In [9]:
%load_ext autoreload
%autoreload 2
%matplotlib inline
import eden
import matplotlib.pyplot as plt
from eden.util import configure_logging
import logging


The autoreload extension is already loaded. To reload it, use:
  %reload_ext autoreload

In [10]:
from itertools import tee, chain, islice
import numpy as np
import random
from time import time
import datetime
from graphlearn.graphlearn import GraphLearnSampler
from eden.util import fit,estimate
from eden.graph import Vectorizer
import random
# get data
from eden.converter.graph.gspan import gspan_to_eden
from itertools import islice
def get_graphs(dataset_fname, size=100):
    return  islice(gspan_to_eden(dataset_fname),size)

In [11]:
def fit_sample(graphs, random_state=42):
    graphs, graphs_ = tee(graphs)
    sampler=GraphLearnSampler(radius_list=[0,1],thickness_list=[2],
                              min_cip_count=2, min_interface_count=2,
                              vectorizer=Vectorizer(5), random_state=random_state)
    
    sampler.fit(graphs, nu=0.25, n_jobs=-1)

    logger.info('graph grammar stats:')
    dataset_size, interface_counts, core_counts, cip_counts = sampler.grammar().size()
    logger.info('#instances:%d   #interfaces: %d   #cores: %d   #core-interface-pairs: %d' % (dataset_size, interface_counts, core_counts, cip_counts))
    graphs = sampler.sample(graphs_,
                            n_steps=5, n_samples=4,
                            target_orig_cip=False,
                            probabilistic_core_choice=False,
                            score_core_choice= False,
                            max_core_size_diff=3,
                            burnin=1,
                            omit_seed=True,
                            max_cycle_size=6,
                            improving_threshold=0.25,
                            accept_static_penalty=0,
                            n_jobs=-1,
                            select_cip_max_tries=200,
                            keep_duplicates=True,
                            generator_mode=True)
    return graphs

In [12]:
def fit_and_evaluate(pos_original, neg_original,
                     pos_sampled, neg_sampled,
                     pos_test, neg_test,
                     random_state=42):
    # create graph sets...orig augmented and sampled
    pos_orig,pos_orig_ = tee(pos_original)
    neg_orig,neg_orig_ = tee(neg_original)
    
    pos_sampled, pos_sampled_ = tee(pos_sampled)
    neg_sampled, neg_sampled_ = tee(neg_sampled)
    
    pos_augmented = chain(pos_orig_,pos_sampled_)
    neg_augmented = chain(neg_orig_,neg_sampled_)

    predictive_performances = []
    for desc,pos_train,neg_train in [('original',pos_orig, neg_orig),
                                     ('sample',pos_sampled,neg_sampled),
                                     ('original+sample',pos_augmented, neg_augmented)]:
        pos_train,pos_train_ = tee(pos_train)
        neg_train,neg_train_ = tee(neg_train)
        pos_size=sum(1 for x in pos_train_)
        neg_size=sum(1 for x in neg_train_)

        logger.info( "-"*80)
        logger.info('working on %s'%(desc))
        logger.info('training set sizes: #pos: %d #neg: %d'%(pos_size, neg_size))

        if pos_size == 0 or neg_size == 0:
            logger.info('WARNING: empty dataset')
            predictive_performances.append(0)            
        else:
            start=time()
            pos_test,pos_test_ = tee(pos_test)
            neg_test,neg_test_ = tee(neg_test)
            local_estimator = fit(pos_train, neg_train, Vectorizer(4), n_jobs=-1, n_iter_search=1)
            apr, roc = estimate(pos_test_, neg_test_, local_estimator, Vectorizer(4))
            predictive_performances.append(roc)
            logger.info( 'elapsed: %.1f sec'%(time()-start))
    return predictive_performances

In [13]:
def evaluate(pos_fname, neg_fname, size=None, percentages=None, n_repetitions=None, train_test_split=None):
    # initializing 
    graphs_pos = get_graphs(pos_fname, size=size)
    graphs_neg = get_graphs(neg_fname, size=size)

    # train/test split
    from eden.util import random_bipartition_iter
    pos_train_global,pos_test_global = random_bipartition_iter(graphs_pos,train_test_split,random_state=random.random()*1000)
    neg_train_global,neg_test_global = random_bipartition_iter(graphs_neg,train_test_split,random_state=random.random()*1000)


    original_repetitions = []
    original_sample_repetitions = []
    sample_repetitions = []

    for percentage in percentages:
        originals = []
        originals_samples = []
        samples = []
        for repetition in range(n_repetitions):
            random_state = int(313379*percentage+repetition) 
            random.seed(random_state)
            pos_train_global,pos_train_global_ = tee(pos_train_global)
            neg_train_global,neg_train_global_ = tee(neg_train_global)
            pos_test_global,pos_test_global_ = tee(pos_test_global)
            neg_test_global,neg_test_global_ = tee(neg_test_global)

            # use shuffled list to create test and sample set
            pos,pos_reminder = random_bipartition_iter(pos_train_global_,percentage)
            pos,pos_ = tee(pos)
            neg,neg_reminder = random_bipartition_iter(neg_train_global_,percentage)
            neg,neg_ = tee(neg)

            #sample independently from the 2 classes
            logger.info('Positive')
            sampled_pos = fit_sample(pos_, random_state=random_state)
            logger.info('Negative')
            sampled_neg = fit_sample(neg_, random_state=random_state)

            #evaluate the predictive performance on held out test set
            start=time()
            logger.info( "="*80)
            logger.info( 'repetition: %d/%d'%(repetition+1, n_repetitions))
            logger.info( "training percentage:"+str(percentage))
            perf_orig,\
            perf_samp,\
            perf_orig_samp = fit_and_evaluate(pos,neg,
                                              sampled_pos,sampled_neg,
                                              pos_test_global_,neg_test_global_)
            logger.info( 'Time elapsed for full repetition: %.1f sec'%((time()-start)))
            originals.append(perf_orig)
            originals_samples.append(perf_orig_samp)
            samples.append(perf_samp)

        original_repetitions.append(originals)
        original_sample_repetitions.append(originals_samples)
        sample_repetitions.append(samples)
    
    return original_repetitions, original_sample_repetitions, sample_repetitions

In [14]:
def plot(dataset, percentages, original_sample_repetitions, original_repetitions, sample_repetitions):
    gc={'color':'g'}
    rc={'color':'r'}
    bc={'color':'b'}
    ws = 0.02
    os = np.mean(original_sample_repetitions, axis=1)
    o = np.mean(original_repetitions, axis=1)
    s = np.mean(sample_repetitions, axis=1)
    plt.figure(figsize=(18,8))
    plt.grid()
    plt.boxplot(original_sample_repetitions, positions=percentages, widths=ws, capprops=gc, medianprops=gc, boxprops=gc, whiskerprops=gc, flierprops=gc)
    plt.plot(percentages,os, color='g', marker='o', markeredgewidth=1, markersize=7, markeredgecolor='g', markerfacecolor='w', label='original+sample')

    plt.boxplot(original_repetitions, positions=percentages, widths=ws, capprops=rc, medianprops=rc, boxprops=rc, whiskerprops=rc, flierprops=rc)
    plt.plot(percentages,o, color='r', marker='o', markeredgewidth=1, markersize=7, markeredgecolor='r', markerfacecolor='w', label='original')

    plt.boxplot(sample_repetitions, positions=percentages, widths=ws, capprops=bc, medianprops=bc, boxprops=bc, whiskerprops=bc, flierprops=bc)
    plt.plot(percentages,s, color='b', marker='o', markeredgewidth=1, markersize=7, markeredgecolor='b', markerfacecolor='w', label='sample')

    plt.xlim(percentages[0]-.05,percentages[-1]+.05)
    plt.title(dataset+'\n',fontsize=17)
    plt.legend(loc='lower right',fontsize=16)
    plt.ylabel('ROC AUC',fontsize=16)
    plt.xlabel('Dataset size (fraction)',fontsize=16)
    plt.savefig('%s_plot_predictive_performance_of_samples.pdf' % dataset)

In [15]:
def save_results(result_fname,percentages, original_repetitions,original_sample_repetitions,sample_repetitions):
    with open(result_fname,'w') as f:
        f.write('dataset sizes list:\n')
        for perc in percentages:
            f.write('%s '% perc)
        f.write('\n')
        f.write('AUC scores:\n')
        for repetitions in original_repetitions,original_sample_repetitions,sample_repetitions:
            f.write('%s\n' % len(repetitions))
            for repetition in repetitions:
                for auc in repetition:
                    f.write('%s ' % auc)
                f.write('\n')
    
def load_results(result_fname):
    with open(result_fname) as f:
        comment = next(f)
        line = next(f)
        percentages = [float(x) for x in line.split()]
        comment = next(f)

        original_repetitions = []
        size = int(next(f))
        for i in range(size):
            line = next(f)
            repetition = [float(x) for x in line.split()]
            original_repetitions.append(repetition)

        original_sample_repetitions = []
        size = int(next(f))
        for i in range(size):
            line = next(f)
            repetition = [float(x) for x in line.split()]
            original_sample_repetitions.append(repetition)


        sample_repetitions = []
        size = int(next(f))
        for i in range(size):
            line = next(f)
            repetition = [float(x) for x in line.split()]
            sample_repetitions.append(repetition)
            
    return percentages, original_repetitions,original_sample_repetitions,sample_repetitions

Experimental pipeline


In [ ]:
%%time
#special case: bursi

dataset='bursi'
#logging
logger = logging.getLogger()
if True:
    logger_fname = '%s_predictive_performance_of_samples.log'%dataset
else:
    logger_fname = None
configure_logging(logger,verbosity=1, filename=logger_fname)

#main 
start=time()
print( 'Working with dataset: %s' % dataset )

logger.info( 'Working with dataset: %s' % dataset )
pos_dataset_fname = 'bursi.pos.gspan'
neg_dataset_fname = 'bursi.neg.gspan'

percentages=[.05,.2,.4,.6,.8,.95]

original_repetitions,\
original_sample_repetitions,\
sample_repetitions = evaluate(pos_dataset_fname,
                              neg_dataset_fname,
                              size=400,
                              percentages=percentages,
                              n_repetitions=10,
                              train_test_split=0.7)
#save and display results
result_fname='%s_predictive_performance_of_samples.data'%dataset
save_results(result_fname,percentages, original_repetitions,original_sample_repetitions,sample_repetitions)    
percentages_l, original_repetitions_l,original_sample_repetitions_l,sample_repetitions_l = load_results(result_fname)
plot(dataset, percentages_l, original_sample_repetitions_l, original_repetitions_l, sample_repetitions_l)

print('Time elapsed: %s'%(datetime.timedelta(seconds=(time() - start))))


Working with dataset: bursi
Working with dataset: bursi
Positive
graph grammar stats:
#instances:14   #interfaces: 4   #cores: 9   #core-interface-pairs: 10
Negative
graph grammar stats:
#instances:14   #interfaces: 9   #cores: 9   #core-interface-pairs: 20
================================================================================
repetition: 1/10
training percentage:0.05
--------------------------------------------------------------------------------
working on original
training set sizes: #pos: 14 #neg: 14
Test set
Instances: 240 ; Features: 1048577 with an avg of 298 features per instance
--------------------------------------------------------------------------------
Test Estimate
             precision    recall  f1-score   support

         -1       0.68      0.67      0.67       120
          1       0.67      0.68      0.68       120

avg / total       0.68      0.68      0.67       240

APR: 0.666
ROC: 0.716
Cross-validated estimate
            accuracy: 0.812 +- 0.026
           precision: 0.841 +- 0.031
              recall: 0.775 +- 0.077
                  f1: 0.803 +- 0.037
   average_precision: 0.852 +- 0.042
             roc_auc: 0.861 +- 0.005
elapsed: 4.6 sec
--------------------------------------------------------------------------------
working on sample
training set sizes: #pos: 16 #neg: 26
Test set
Instances: 240 ; Features: 1048577 with an avg of 298 features per instance
--------------------------------------------------------------------------------
Test Estimate
             precision    recall  f1-score   support

         -1       0.64      0.72      0.68       120
          1       0.69      0.60      0.64       120

avg / total       0.67      0.66      0.66       240

APR: 0.717
ROC: 0.729
Cross-validated estimate
            accuracy: 0.800 +- 0.039
           precision: 0.838 +- 0.058
              recall: 0.750 +- 0.065
                  f1: 0.789 +- 0.043
   average_precision: 0.848 +- 0.036
             roc_auc: 0.856 +- 0.017
elapsed: 4.4 sec
--------------------------------------------------------------------------------
working on original+sample
training set sizes: #pos: 30 #neg: 40
Test set
Instances: 240 ; Features: 1048577 with an avg of 298 features per instance
--------------------------------------------------------------------------------
Test Estimate
             precision    recall  f1-score   support

         -1       0.69      0.67      0.68       120
          1       0.68      0.70      0.69       120

avg / total       0.68      0.68      0.68       240

APR: 0.704
ROC: 0.736
Cross-validated estimate
            accuracy: 0.804 +- 0.049
           precision: 0.840 +- 0.021
              recall: 0.750 +- 0.105
                  f1: 0.789 +- 0.070
   average_precision: 0.850 +- 0.008
             roc_auc: 0.857 +- 0.018
elapsed: 4.5 sec
Time elapsed: 20.0 sec
Positive
graph grammar stats:
#instances:14   #interfaces: 4   #cores: 9   #core-interface-pairs: 10
Negative
graph grammar stats:
#instances:14   #interfaces: 9   #cores: 9   #core-interface-pairs: 20
================================================================================
repetition: 2/10
training percentage:0.05
--------------------------------------------------------------------------------
working on original
training set sizes: #pos: 14 #neg: 14
Test set
Instances: 240 ; Features: 1048577 with an avg of 298 features per instance
--------------------------------------------------------------------------------
Test Estimate
             precision    recall  f1-score   support

         -1       0.76      0.56      0.64       120
          1       0.65      0.82      0.73       120

avg / total       0.71      0.69      0.69       240

APR: 0.678
ROC: 0.730
Cross-validated estimate
            accuracy: 0.796 +- 0.033
           precision: 0.837 +- 0.048
              recall: 0.742 +- 0.085
                  f1: 0.782 +- 0.047
   average_precision: 0.866 +- 0.016
             roc_auc: 0.867 +- 0.013
elapsed: 4.2 sec
--------------------------------------------------------------------------------
working on sample
training set sizes: #pos: 16 #neg: 25
Test set
Instances: 240 ; Features: 1048577 with an avg of 298 features per instance
--------------------------------------------------------------------------------
Test Estimate
             precision    recall  f1-score   support

         -1       0.73      0.61      0.66       120
          1       0.66      0.78      0.72       120

avg / total       0.70      0.69      0.69       240

APR: 0.679
ROC: 0.728
Cross-validated estimate
            accuracy: 0.800 +- 0.028
           precision: 0.860 +- 0.053
              recall: 0.725 +- 0.077
                  f1: 0.782 +- 0.040
   average_precision: 0.857 +- 0.036
             roc_auc: 0.861 +- 0.012
elapsed: 4.1 sec
--------------------------------------------------------------------------------
working on original+sample
training set sizes: #pos: 30 #neg: 39
Test set
Instances: 240 ; Features: 1048577 with an avg of 298 features per instance
--------------------------------------------------------------------------------
Test Estimate
             precision    recall  f1-score   support

         -1       0.69      0.72      0.70       120
          1       0.71      0.68      0.69       120

avg / total       0.70      0.70      0.70       240

APR: 0.723
ROC: 0.751
Cross-validated estimate
            accuracy: 0.800 +- 0.043
           precision: 0.834 +- 0.038
              recall: 0.750 +- 0.087
                  f1: 0.787 +- 0.057
   average_precision: 0.861 +- 0.023
             roc_auc: 0.857 +- 0.007
elapsed: 4.3 sec
Time elapsed: 18.8 sec
Positive
graph grammar stats:
#instances:14   #interfaces: 4   #cores: 9   #core-interface-pairs: 10
Negative
graph grammar stats:
#instances:14   #interfaces: 9   #cores: 9   #core-interface-pairs: 20
================================================================================
repetition: 3/10
training percentage:0.05
--------------------------------------------------------------------------------
working on original
training set sizes: #pos: 14 #neg: 14
Test set
Instances: 240 ; Features: 1048577 with an avg of 298 features per instance
--------------------------------------------------------------------------------
Test Estimate
             precision    recall  f1-score   support

         -1       0.68      0.66      0.67       120
          1       0.67      0.68      0.67       120

avg / total       0.67      0.67      0.67       240

APR: 0.712
ROC: 0.735
Cross-validated estimate
            accuracy: 0.796 +- 0.031
           precision: 0.840 +- 0.055
              recall: 0.742 +- 0.085
                  f1: 0.782 +- 0.039
   average_precision: 0.861 +- 0.037
             roc_auc: 0.870 +- 0.016
elapsed: 4.2 sec
--------------------------------------------------------------------------------
working on sample
training set sizes: #pos: 16 #neg: 25
Test set
Instances: 240 ; Features: 1048577 with an avg of 298 features per instance
--------------------------------------------------------------------------------
Test Estimate
             precision    recall  f1-score   support

         -1       0.69      0.76      0.73       120
          1       0.73      0.67      0.70       120

avg / total       0.71      0.71      0.71       240

APR: 0.766
ROC: 0.775
Cross-validated estimate
            accuracy: 0.804 +- 0.041
           precision: 0.831 +- 0.039
              recall: 0.767 +- 0.094
                  f1: 0.794 +- 0.057
   average_precision: 0.861 +- 0.024
             roc_auc: 0.860 +- 0.012
elapsed: 4.2 sec
--------------------------------------------------------------------------------
working on original+sample
training set sizes: #pos: 30 #neg: 39
Test set
Instances: 240 ; Features: 1048577 with an avg of 298 features per instance
--------------------------------------------------------------------------------
Test Estimate
             precision    recall  f1-score   support

         -1       0.68      0.72      0.70       120
          1       0.70      0.66      0.68       120

avg / total       0.69      0.69      0.69       240

APR: 0.748
ROC: 0.760
Cross-validated estimate
            accuracy: 0.800 +- 0.028
           precision: 0.824 +- 0.028
              recall: 0.767 +- 0.082
                  f1: 0.791 +- 0.041
   average_precision: 0.864 +- 0.017
             roc_auc: 0.866 +- 0.007
elapsed: 4.5 sec
Time elapsed: 18.9 sec
Positive
graph grammar stats:
#instances:14   #interfaces: 4   #cores: 9   #core-interface-pairs: 10
Negative
graph grammar stats:
#instances:14   #interfaces: 9   #cores: 9   #core-interface-pairs: 20
================================================================================
repetition: 4/10
training percentage:0.05
--------------------------------------------------------------------------------
working on original
training set sizes: #pos: 14 #neg: 14
Test set
Instances: 240 ; Features: 1048577 with an avg of 298 features per instance
--------------------------------------------------------------------------------
Test Estimate
             precision    recall  f1-score   support

         -1       0.68      0.66      0.67       120
          1       0.67      0.69      0.68       120

avg / total       0.68      0.68      0.67       240

APR: 0.703
ROC: 0.724
Cross-validated estimate
            accuracy: 0.796 +- 0.050
           precision: 0.840 +- 0.026
              recall: 0.733 +- 0.128
                  f1: 0.776 +- 0.078
   average_precision: 0.870 +- 0.017
             roc_auc: 0.860 +- 0.024
elapsed: 4.1 sec
--------------------------------------------------------------------------------
working on sample
training set sizes: #pos: 16 #neg: 25
Test set
Instances: 240 ; Features: 1048577 with an avg of 298 features per instance
--------------------------------------------------------------------------------
Test Estimate
             precision    recall  f1-score   support

         -1       0.72      0.66      0.69       120
          1       0.69      0.75      0.72       120

avg / total       0.71      0.70      0.70       240

APR: 0.729
ROC: 0.750
Cross-validated estimate
            accuracy: 0.804 +- 0.031
           precision: 0.832 +- 0.037
              recall: 0.767 +- 0.082
                  f1: 0.795 +- 0.043
   average_precision: 0.855 +- 0.018
             roc_auc: 0.860 +- 0.019
elapsed: 4.6 sec
--------------------------------------------------------------------------------
working on original+sample
training set sizes: #pos: 30 #neg: 39
Test set
Instances: 240 ; Features: 1048577 with an avg of 298 features per instance
--------------------------------------------------------------------------------
Test Estimate
             precision    recall  f1-score   support

         -1       0.65      0.72      0.68       120
          1       0.69      0.62      0.65       120

avg / total       0.67      0.67      0.67       240

APR: 0.715
ROC: 0.736
Cross-validated estimate
            accuracy: 0.808 +- 0.042
           precision: 0.826 +- 0.029
              recall: 0.783 +- 0.103
                  f1: 0.800 +- 0.060
   average_precision: 0.864 +- 0.025
             roc_auc: 0.870 +- 0.013
elapsed: 4.6 sec
Time elapsed: 19.0 sec
Positive
graph grammar stats:
#instances:14   #interfaces: 4   #cores: 9   #core-interface-pairs: 10
Negative
graph grammar stats:
#instances:14   #interfaces: 9   #cores: 9   #core-interface-pairs: 20
================================================================================
repetition: 5/10
training percentage:0.05
--------------------------------------------------------------------------------
working on original
training set sizes: #pos: 14 #neg: 14
Test set
Instances: 240 ; Features: 1048577 with an avg of 298 features per instance
--------------------------------------------------------------------------------
Test Estimate
             precision    recall  f1-score   support

         -1       0.73      0.60      0.66       120
          1       0.66      0.78      0.71       120

avg / total       0.69      0.69      0.69       240

APR: 0.677
ROC: 0.736
Cross-validated estimate
            accuracy: 0.804 +- 0.025
           precision: 0.851 +- 0.066
              recall: 0.750 +- 0.065
                  f1: 0.792 +- 0.028
   average_precision: 0.859 +- 0.033
             roc_auc: 0.864 +- 0.018
elapsed: 4.5 sec
--------------------------------------------------------------------------------
working on sample
training set sizes: #pos: 16 #neg: 26
Test set
Instances: 240 ; Features: 1048577 with an avg of 298 features per instance
--------------------------------------------------------------------------------
Test Estimate
             precision    recall  f1-score   support

         -1       0.60      0.75      0.67       120
          1       0.67      0.50      0.57       120

avg / total       0.63      0.62      0.62       240

APR: 0.655
ROC: 0.697
Cross-validated estimate
            accuracy: 0.796 +- 0.040
           precision: 0.848 +- 0.040
              recall: 0.725 +- 0.094
                  f1: 0.777 +- 0.059
   average_precision: 0.847 +- 0.041
             roc_auc: 0.851 +- 0.012
elapsed: 4.4 sec
--------------------------------------------------------------------------------
working on original+sample
training set sizes: #pos: 30 #neg: 40
Test set
Instances: 240 ; Features: 1048577 with an avg of 298 features per instance
--------------------------------------------------------------------------------
Test Estimate
             precision    recall  f1-score   support

         -1       0.75      0.64      0.69       120
          1       0.69      0.79      0.74       120

avg / total       0.72      0.72      0.72       240

APR: 0.692
ROC: 0.750
Cross-validated estimate
            accuracy: 0.788 +- 0.044
           precision: 0.823 +- 0.040
              recall: 0.733 +- 0.094
                  f1: 0.773 +- 0.059
   average_precision: 0.851 +- 0.028
             roc_auc: 0.855 +- 0.009
elapsed: 4.4 sec
Time elapsed: 19.1 sec
Positive
graph grammar stats:
#instances:14   #interfaces: 4   #cores: 9   #core-interface-pairs: 10
Negative
graph grammar stats:
#instances:14   #interfaces: 9   #cores: 9   #core-interface-pairs: 20
================================================================================
repetition: 6/10
training percentage:0.05
--------------------------------------------------------------------------------
working on original
training set sizes: #pos: 14 #neg: 14
Test set
Instances: 240 ; Features: 1048577 with an avg of 298 features per instance
--------------------------------------------------------------------------------
Test Estimate
             precision    recall  f1-score   support

         -1       0.70      0.68      0.69       120
          1       0.69      0.72      0.70       120

avg / total       0.70      0.70      0.70       240

APR: 0.729
ROC: 0.746
Cross-validated estimate
            accuracy: 0.804 +- 0.028
           precision: 0.835 +- 0.015
              recall: 0.758 +- 0.067
                  f1: 0.793 +- 0.040
   average_precision: 0.866 +- 0.028
             roc_auc: 0.869 +- 0.021
elapsed: 4.2 sec
--------------------------------------------------------------------------------
working on sample
training set sizes: #pos: 16 #neg: 25
Test set
Instances: 240 ; Features: 1048577 with an avg of 298 features per instance
--------------------------------------------------------------------------------
Test Estimate
             precision    recall  f1-score   support

         -1       0.73      0.56      0.63       120
          1       0.64      0.79      0.71       120

avg / total       0.69      0.68      0.67       240

APR: 0.753
ROC: 0.767
Cross-validated estimate
            accuracy: 0.792 +- 0.035
           precision: 0.836 +- 0.039
              recall: 0.733 +- 0.111
                  f1: 0.774 +- 0.058
   average_precision: 0.849 +- 0.028
             roc_auc: 0.853 +- 0.012
elapsed: 4.2 sec
--------------------------------------------------------------------------------
working on original+sample
training set sizes: #pos: 30 #neg: 39
Test set
Instances: 240 ; Features: 1048577 with an avg of 298 features per instance
--------------------------------------------------------------------------------
Test Estimate
             precision    recall  f1-score   support

         -1       0.68      0.63      0.66       120
          1       0.66      0.70      0.68       120

avg / total       0.67      0.67      0.67       240

APR: 0.694
ROC: 0.722
Cross-validated estimate
            accuracy: 0.817 +- 0.024
           precision: 0.865 +- 0.043
              recall: 0.758 +- 0.093
                  f1: 0.802 +- 0.043
   average_precision: 0.858 +- 0.021
             roc_auc: 0.859 +- 0.005
elapsed: 4.5 sec
Time elapsed: 19.4 sec
Positive
graph grammar stats:
#instances:14   #interfaces: 4   #cores: 9   #core-interface-pairs: 10
Negative
graph grammar stats:
#instances:14   #interfaces: 9   #cores: 9   #core-interface-pairs: 20
================================================================================
repetition: 7/10
training percentage:0.05
--------------------------------------------------------------------------------
working on original
training set sizes: #pos: 14 #neg: 14
Test set
Instances: 240 ; Features: 1048577 with an avg of 298 features per instance
--------------------------------------------------------------------------------
Test Estimate
             precision    recall  f1-score   support

         -1       0.71      0.64      0.67       120
          1       0.67      0.73      0.70       120

avg / total       0.69      0.69      0.69       240

APR: 0.695
ROC: 0.723
Cross-validated estimate
            accuracy: 0.808 +- 0.048
           precision: 0.845 +- 0.027
              recall: 0.758 +- 0.122
                  f1: 0.793 +- 0.071
   average_precision: 0.853 +- 0.019
             roc_auc: 0.859 +- 0.015
elapsed: 4.3 sec
--------------------------------------------------------------------------------
working on sample
training set sizes: #pos: 16 #neg: 26
Test set
Instances: 240 ; Features: 1048577 with an avg of 298 features per instance
--------------------------------------------------------------------------------
Test Estimate
             precision    recall  f1-score   support

         -1       0.69      0.71      0.70       120
          1       0.70      0.68      0.69       120

avg / total       0.70      0.70      0.70       240

APR: 0.702
ROC: 0.736
Cross-validated estimate
            accuracy: 0.808 +- 0.036
           precision: 0.838 +- 0.035
              recall: 0.767 +- 0.082
                  f1: 0.798 +- 0.047
   average_precision: 0.872 +- 0.032
             roc_auc: 0.872 +- 0.011
elapsed: 4.2 sec
--------------------------------------------------------------------------------
working on original+sample
training set sizes: #pos: 30 #neg: 40
Test set
Instances: 240 ; Features: 1048577 with an avg of 298 features per instance
--------------------------------------------------------------------------------
Test Estimate
             precision    recall  f1-score   support

         -1       0.67      0.82      0.74       120
          1       0.77      0.60      0.67       120

avg / total       0.72      0.71      0.70       240

APR: 0.729
ROC: 0.766
Cross-validated estimate
            accuracy: 0.808 +- 0.033
           precision: 0.842 +- 0.041
              recall: 0.767 +- 0.101
                  f1: 0.797 +- 0.051
   average_precision: 0.863 +- 0.007
             roc_auc: 0.865 +- 0.018
elapsed: 4.4 sec
Time elapsed: 19.0 sec
Positive
graph grammar stats:
#instances:14   #interfaces: 4   #cores: 9   #core-interface-pairs: 10
Negative
graph grammar stats:
#instances:14   #interfaces: 9   #cores: 9   #core-interface-pairs: 20
================================================================================
repetition: 8/10
training percentage:0.05
--------------------------------------------------------------------------------
working on original
training set sizes: #pos: 14 #neg: 14
Test set
Instances: 240 ; Features: 1048577 with an avg of 298 features per instance
--------------------------------------------------------------------------------
Test Estimate
             precision    recall  f1-score   support

         -1       0.65      0.72      0.68       120
          1       0.68      0.61      0.64       120

avg / total       0.66      0.66      0.66       240

APR: 0.685
ROC: 0.712
Cross-validated estimate
            accuracy: 0.812 +- 0.040
           precision: 0.854 +- 0.039
              recall: 0.758 +- 0.093
                  f1: 0.799 +- 0.055
   average_precision: 0.860 +- 0.013
             roc_auc: 0.859 +- 0.023
elapsed: 4.1 sec
--------------------------------------------------------------------------------
working on sample
training set sizes: #pos: 14 #neg: 26
Test set
Instances: 240 ; Features: 1048577 with an avg of 298 features per instance
--------------------------------------------------------------------------------
Test Estimate
             precision    recall  f1-score   support

         -1       0.59      0.72      0.64       120
          1       0.63      0.49      0.55       120

avg / total       0.61      0.60      0.60       240

APR: 0.642
ROC: 0.699
Cross-validated estimate
            accuracy: 0.796 +- 0.038
           precision: 0.816 +- 0.035
              recall: 0.767 +- 0.090
                  f1: 0.787 +- 0.050
   average_precision: 0.861 +- 0.025
             roc_auc: 0.862 +- 0.009
elapsed: 4.2 sec
--------------------------------------------------------------------------------
working on original+sample
training set sizes: #pos: 28 #neg: 40
Test set
Instances: 240 ; Features: 1048577 with an avg of 298 features per instance
--------------------------------------------------------------------------------
Test Estimate
             precision    recall  f1-score   support

         -1       0.71      0.68      0.70       120
          1       0.70      0.72      0.71       120

avg / total       0.70      0.70      0.70       240

APR: 0.720
ROC: 0.757
Cross-validated estimate
            accuracy: 0.812 +- 0.046
           precision: 0.840 +- 0.041
              recall: 0.775 +- 0.097
                  f1: 0.802 +- 0.061
   average_precision: 0.862 +- 0.030
             roc_auc: 0.854 +- 0.020
elapsed: 4.4 sec
Time elapsed: 18.7 sec
Positive
graph grammar stats:
#instances:14   #interfaces: 4   #cores: 9   #core-interface-pairs: 10
Negative
graph grammar stats:
#instances:14   #interfaces: 9   #cores: 9   #core-interface-pairs: 20
================================================================================
repetition: 9/10
training percentage:0.05
--------------------------------------------------------------------------------
working on original
training set sizes: #pos: 14 #neg: 14
Test set
Instances: 240 ; Features: 1048577 with an avg of 298 features per instance
--------------------------------------------------------------------------------
Test Estimate
             precision    recall  f1-score   support

         -1       0.67      0.64      0.66       120
          1       0.66      0.68      0.67       120

avg / total       0.66      0.66      0.66       240

APR: 0.714
ROC: 0.735
Cross-validated estimate
            accuracy: 0.796 +- 0.036
           precision: 0.840 +- 0.019
              recall: 0.733 +- 0.101
                  f1: 0.778 +- 0.058
   average_precision: 0.850 +- 0.038
             roc_auc: 0.856 +- 0.009
elapsed: 4.6 sec
--------------------------------------------------------------------------------
working on sample
training set sizes: #pos: 16 #neg: 25
Test set
Instances: 240 ; Features: 1048577 with an avg of 298 features per instance
--------------------------------------------------------------------------------
Test Estimate
             precision    recall  f1-score   support

         -1       0.67      0.69      0.68       120
          1       0.68      0.67      0.68       120

avg / total       0.68      0.68      0.68       240

APR: 0.721
ROC: 0.739
Cross-validated estimate
            accuracy: 0.812 +- 0.037
           precision: 0.845 +- 0.028
              recall: 0.767 +- 0.086
                  f1: 0.801 +- 0.050
   average_precision: 0.864 +- 0.027
             roc_auc: 0.871 +- 0.020
elapsed: 4.2 sec
--------------------------------------------------------------------------------
working on original+sample
training set sizes: #pos: 30 #neg: 39
Test set
Instances: 240 ; Features: 1048577 with an avg of 298 features per instance
--------------------------------------------------------------------------------
Test Estimate
             precision    recall  f1-score   support

         -1       0.71      0.77      0.74       120
          1       0.75      0.69      0.72       120

avg / total       0.73      0.73      0.73       240

APR: 0.752
ROC: 0.782
Cross-validated estimate
            accuracy: 0.804 +- 0.043
           precision: 0.817 +- 0.035
              recall: 0.783 +- 0.072
                  f1: 0.799 +- 0.050
   average_precision: 0.862 +- 0.022
             roc_auc: 0.869 +- 0.016
elapsed: 4.3 sec
Time elapsed: 19.0 sec
Positive
graph grammar stats:
#instances:14   #interfaces: 4   #cores: 9   #core-interface-pairs: 10
Negative
graph grammar stats:
#instances:14   #interfaces: 9   #cores: 9   #core-interface-pairs: 20
================================================================================
repetition: 10/10
training percentage:0.05
--------------------------------------------------------------------------------
working on original
training set sizes: #pos: 14 #neg: 14
Test set
Instances: 240 ; Features: 1048577 with an avg of 298 features per instance
--------------------------------------------------------------------------------
Test Estimate
             precision    recall  f1-score   support

         -1       0.65      0.68      0.67       120
          1       0.67      0.63      0.65       120

avg / total       0.66      0.66      0.66       240

APR: 0.700
ROC: 0.720
Cross-validated estimate
            accuracy: 0.833 +- 0.042
           precision: 0.855 +- 0.043
              recall: 0.808 +- 0.101
                  f1: 0.826 +- 0.054
   average_precision: 0.863 +- 0.039
             roc_auc: 0.870 +- 0.010
elapsed: 4.2 sec
--------------------------------------------------------------------------------
working on sample
training set sizes: #pos: 16 #neg: 25
Test set
Instances: 240 ; Features: 1048577 with an avg of 298 features per instance
--------------------------------------------------------------------------------
Test Estimate
             precision    recall  f1-score   support

         -1       0.64      0.85      0.73       120
          1       0.78      0.52      0.62       120

avg / total       0.71      0.68      0.67       240

APR: 0.713
ROC: 0.748
Cross-validated estimate
            accuracy: 0.792 +- 0.037
           precision: 0.824 +- 0.036
              recall: 0.750 +- 0.118
                  f1: 0.778 +- 0.061
   average_precision: 0.870 +- 0.010
             roc_auc: 0.866 +- 0.016
elapsed: 4.3 sec
--------------------------------------------------------------------------------
working on original+sample
training set sizes: #pos: 30 #neg: 39
Test set
Instances: 240 ; Features: 1048577 with an avg of 298 features per instance
--------------------------------------------------------------------------------
Test Estimate
             precision    recall  f1-score   support

         -1       0.67      0.80      0.73       120
          1       0.75      0.61      0.67       120

avg / total       0.71      0.70      0.70       240

APR: 0.692
ROC: 0.740
Cross-validated estimate
            accuracy: 0.808 +- 0.040
           precision: 0.847 +- 0.035
              recall: 0.758 +- 0.113
                  f1: 0.794 +- 0.059
   average_precision: 0.849 +- 0.016
             roc_auc: 0.857 +- 0.014
elapsed: 4.2 sec
Time elapsed: 18.6 sec
Positive
graph grammar stats:
#instances:56   #interfaces: 23   #cores: 25   #core-interface-pairs: 65
Negative
graph grammar stats:
#instances:56   #interfaces: 38   #cores: 33   #core-interface-pairs: 104
================================================================================
repetition: 1/10
training percentage:0.2
--------------------------------------------------------------------------------
working on original
training set sizes: #pos: 56 #neg: 56
Test set
Instances: 240 ; Features: 1048577 with an avg of 298 features per instance
--------------------------------------------------------------------------------
Test Estimate
             precision    recall  f1-score   support

         -1       0.78      0.78      0.78       120
          1       0.78      0.78      0.78       120

avg / total       0.78      0.78      0.78       240

APR: 0.804
ROC: 0.825
Cross-validated estimate
            accuracy: 0.800 +- 0.039
           precision: 0.842 +- 0.034
              recall: 0.742 +- 0.089
                  f1: 0.785 +- 0.053
   average_precision: 0.864 +- 0.010
             roc_auc: 0.860 +- 0.018
elapsed: 4.9 sec
--------------------------------------------------------------------------------
working on sample
training set sizes: #pos: 106 #neg: 106
Test set
Instances: 240 ; Features: 1048577 with an avg of 298 features per instance
--------------------------------------------------------------------------------
Test Estimate
             precision    recall  f1-score   support

         -1       0.69      0.70      0.69       120
          1       0.69      0.68      0.69       120

avg / total       0.69      0.69      0.69       240

APR: 0.748
ROC: 0.757
Cross-validated estimate
            accuracy: 0.796 +- 0.036
           precision: 0.843 +- 0.034
              recall: 0.733 +- 0.107
                  f1: 0.778 +- 0.058
   average_precision: 0.850 +- 0.029
             roc_auc: 0.857 +- 0.013
elapsed: 7.1 sec
--------------------------------------------------------------------------------
working on original+sample
training set sizes: #pos: 162 #neg: 162
Test set
Instances: 240 ; Features: 1048577 with an avg of 298 features per instance
--------------------------------------------------------------------------------
Test Estimate
             precision    recall  f1-score   support

         -1       0.74      0.77      0.75       120
          1       0.76      0.73      0.75       120

avg / total       0.75      0.75      0.75       240

APR: 0.777
ROC: 0.812
Cross-validated estimate
            accuracy: 0.821 +- 0.045
           precision: 0.841 +- 0.043
              recall: 0.792 +- 0.070
                  f1: 0.814 +- 0.051
   average_precision: 0.860 +- 0.044
             roc_auc: 0.863 +- 0.015
elapsed: 8.0 sec
Time elapsed: 29.3 sec
Positive
graph grammar stats:
#instances:56   #interfaces: 23   #cores: 25   #core-interface-pairs: 65
Negative
graph grammar stats:
#instances:56   #interfaces: 38   #cores: 33   #core-interface-pairs: 104
================================================================================
repetition: 2/10
training percentage:0.2
--------------------------------------------------------------------------------
working on original
training set sizes: #pos: 56 #neg: 56
Test set
Instances: 240 ; Features: 1048577 with an avg of 298 features per instance
--------------------------------------------------------------------------------
Test Estimate
             precision    recall  f1-score   support

         -1       0.75      0.78      0.76       120
          1       0.77      0.74      0.75       120

avg / total       0.76      0.76      0.76       240

APR: 0.798
ROC: 0.815
Cross-validated estimate
            accuracy: 0.821 +- 0.021
           precision: 0.851 +- 0.040
              recall: 0.783 +- 0.061
                  f1: 0.813 +- 0.028
   average_precision: 0.861 +- 0.021
             roc_auc: 0.862 +- 0.011
elapsed: 5.3 sec
--------------------------------------------------------------------------------
working on sample
training set sizes: #pos: 106 #neg: 106
Test set
Instances: 240 ; Features: 1048577 with an avg of 298 features per instance
--------------------------------------------------------------------------------
Test Estimate
             precision    recall  f1-score   support

         -1       0.70      0.69      0.70       120
          1       0.70      0.71      0.70       120

avg / total       0.70      0.70      0.70       240

APR: 0.735
ROC: 0.769
Cross-validated estimate
            accuracy: 0.787 +- 0.033
           precision: 0.808 +- 0.029
              recall: 0.758 +- 0.100
                  f1: 0.778 +- 0.051
   average_precision: 0.842 +- 0.030
             roc_auc: 0.849 +- 0.013
elapsed: 5.6 sec
--------------------------------------------------------------------------------
working on original+sample
training set sizes: #pos: 162 #neg: 162
Test set
Instances: 240 ; Features: 1048577 with an avg of 298 features per instance
--------------------------------------------------------------------------------
Test Estimate
             precision    recall  f1-score   support

         -1       0.70      0.72      0.71       120
          1       0.71      0.70      0.71       120

avg / total       0.71      0.71      0.71       240

APR: 0.750
ROC: 0.788
Cross-validated estimate
            accuracy: 0.804 +- 0.049
           precision: 0.840 +- 0.041
              recall: 0.750 +- 0.087
                  f1: 0.791 +- 0.062
   average_precision: 0.856 +- 0.038
             roc_auc: 0.865 +- 0.023
elapsed: 5.9 sec
Time elapsed: 24.9 sec
Positive
graph grammar stats:
#instances:56   #interfaces: 23   #cores: 25   #core-interface-pairs: 65
Negative
graph grammar stats:
#instances:56   #interfaces: 38   #cores: 33   #core-interface-pairs: 104
================================================================================
repetition: 3/10
training percentage:0.2
--------------------------------------------------------------------------------
working on original
training set sizes: #pos: 56 #neg: 56
Test set
Instances: 240 ; Features: 1048577 with an avg of 298 features per instance
--------------------------------------------------------------------------------
Test Estimate
             precision    recall  f1-score   support

         -1       0.73      0.73      0.73       120
          1       0.73      0.73      0.73       120

avg / total       0.73      0.73      0.73       240

APR: 0.785
ROC: 0.806
Cross-validated estimate
            accuracy: 0.812 +- 0.032
           precision: 0.847 +- 0.027
              recall: 0.767 +- 0.094
                  f1: 0.800 +- 0.050
   average_precision: 0.849 +- 0.025
             roc_auc: 0.861 +- 0.015
elapsed: 4.8 sec
--------------------------------------------------------------------------------
working on sample
training set sizes: #pos: 106 #neg: 106
Test set
Instances: 240 ; Features: 1048577 with an avg of 298 features per instance
--------------------------------------------------------------------------------
Test Estimate
             precision    recall  f1-score   support

         -1       0.65      0.73      0.69       120
          1       0.70      0.61      0.65       120

avg / total       0.67      0.67      0.67       240

APR: 0.737
ROC: 0.735
Cross-validated estimate
            accuracy: 0.817 +- 0.028
           precision: 0.871 +- 0.042
              recall: 0.750 +- 0.087
                  f1: 0.801 +- 0.044
   average_precision: 0.855 +- 0.032
             roc_auc: 0.862 +- 0.015
elapsed: 5.7 sec
--------------------------------------------------------------------------------
working on original+sample
training set sizes: #pos: 162 #neg: 162
Test set
Instances: 240 ; Features: 1048577 with an avg of 298 features per instance
--------------------------------------------------------------------------------
Test Estimate
             precision    recall  f1-score   support

         -1       0.72      0.82      0.76       120
          1       0.79      0.68      0.73       120

avg / total       0.75      0.75      0.74       240

APR: 0.815
ROC: 0.814
Cross-validated estimate
            accuracy: 0.812 +- 0.029
           precision: 0.842 +- 0.042
              recall: 0.775 +- 0.073
                  f1: 0.804 +- 0.037
   average_precision: 0.868 +- 0.025
             roc_auc: 0.870 +- 0.012
elapsed: 6.3 sec
Time elapsed: 24.8 sec
Positive
graph grammar stats:
#instances:56   #interfaces: 23   #cores: 25   #core-interface-pairs: 65
Negative
graph grammar stats:
#instances:56   #interfaces: 38   #cores: 33   #core-interface-pairs: 104
================================================================================
repetition: 4/10
training percentage:0.2
--------------------------------------------------------------------------------
working on original
training set sizes: #pos: 56 #neg: 56
Test set
Instances: 240 ; Features: 1048577 with an avg of 298 features per instance
--------------------------------------------------------------------------------
Test Estimate
             precision    recall  f1-score   support

         -1       0.73      0.78      0.76       120
          1       0.77      0.72      0.74       120

avg / total       0.75      0.75      0.75       240

APR: 0.781
ROC: 0.798
Cross-validated estimate
            accuracy: 0.812 +- 0.051
           precision: 0.838 +- 0.042
              recall: 0.775 +- 0.097
                  f1: 0.802 +- 0.062
   average_precision: 0.859 +- 0.039
             roc_auc: 0.864 +- 0.009
elapsed: 4.6 sec
--------------------------------------------------------------------------------
working on sample
training set sizes: #pos: 106 #neg: 106
Test set
Instances: 240 ; Features: 1048577 with an avg of 298 features per instance
--------------------------------------------------------------------------------
Test Estimate
             precision    recall  f1-score   support

         -1       0.71      0.78      0.74       120
          1       0.75      0.68      0.72       120

avg / total       0.73      0.73      0.73       240

APR: 0.757
ROC: 0.773
Cross-validated estimate
            accuracy: 0.800 +- 0.039
           precision: 0.828 +- 0.017
              recall: 0.758 +- 0.100
                  f1: 0.788 +- 0.057
   average_precision: 0.851 +- 0.042
             roc_auc: 0.866 +- 0.003
elapsed: 7.0 sec
--------------------------------------------------------------------------------
working on original+sample
training set sizes: #pos: 162 #neg: 162
Test set
Instances: 240 ; Features: 1048577 with an avg of 298 features per instance
--------------------------------------------------------------------------------
Test Estimate
             precision    recall  f1-score   support

         -1       0.73      0.76      0.75       120
          1       0.75      0.72      0.74       120

avg / total       0.74      0.74      0.74       240

APR: 0.808
ROC: 0.817
Cross-validated estimate
            accuracy: 0.796 +- 0.036
           precision: 0.821 +- 0.020
              recall: 0.758 +- 0.100
                  f1: 0.784 +- 0.054
   average_precision: 0.852 +- 0.035
             roc_auc: 0.855 +- 0.019
elapsed: 8.4 sec
Time elapsed: 29.0 sec
Positive
graph grammar stats:
#instances:56   #interfaces: 23   #cores: 25   #core-interface-pairs: 65
Negative
graph grammar stats:
#instances:56   #interfaces: 38   #cores: 33   #core-interface-pairs: 104
================================================================================
repetition: 5/10
training percentage:0.2
--------------------------------------------------------------------------------
working on original
training set sizes: #pos: 56 #neg: 56
Test set
Instances: 240 ; Features: 1048577 with an avg of 298 features per instance
--------------------------------------------------------------------------------
Test Estimate
             precision    recall  f1-score   support

         -1       0.75      0.79      0.77       120
          1       0.78      0.74      0.76       120

avg / total       0.77      0.77      0.77       240

APR: 0.833
ROC: 0.835
Cross-validated estimate
            accuracy: 0.825 +- 0.028
           precision: 0.851 +- 0.019
              recall: 0.792 +- 0.087
                  f1: 0.816 +- 0.044
   average_precision: 0.859 +- 0.037
             roc_auc: 0.865 +- 0.009
elapsed: 4.9 sec
--------------------------------------------------------------------------------
working on sample
training set sizes: #pos: 106 #neg: 106
Test set
Instances: 240 ; Features: 1048577 with an avg of 298 features per instance
--------------------------------------------------------------------------------
Test Estimate
             precision    recall  f1-score   support

         -1       0.69      0.72      0.70       120
          1       0.70      0.68      0.69       120

avg / total       0.70      0.70      0.70       240

APR: 0.751
ROC: 0.750
Cross-validated estimate
            accuracy: 0.808 +- 0.020
           precision: 0.862 +- 0.046
              recall: 0.742 +- 0.081
                  f1: 0.792 +- 0.037
   average_precision: 0.862 +- 0.027
             roc_auc: 0.868 +- 0.012
elapsed: 5.3 sec
--------------------------------------------------------------------------------
working on original+sample
training set sizes: #pos: 162 #neg: 162
Test set
Instances: 240 ; Features: 1048577 with an avg of 298 features per instance
--------------------------------------------------------------------------------
Test Estimate
             precision    recall  f1-score   support

         -1       0.73      0.78      0.75       120
          1       0.76      0.71      0.73       120

avg / total       0.74      0.74      0.74       240

APR: 0.792
ROC: 0.812
Cross-validated estimate
            accuracy: 0.796 +- 0.044
           precision: 0.839 +- 0.041
              recall: 0.733 +- 0.082
                  f1: 0.780 +- 0.057
   average_precision: 0.862 +- 0.029
             roc_auc: 0.863 +- 0.015
elapsed: 6.1 sec
Time elapsed: 24.1 sec
Positive
graph grammar stats:
#instances:56   #interfaces: 23   #cores: 25   #core-interface-pairs: 65
Negative
graph grammar stats:
#instances:56   #interfaces: 38   #cores: 33   #core-interface-pairs: 104
================================================================================
repetition: 6/10
training percentage:0.2
--------------------------------------------------------------------------------
working on original
training set sizes: #pos: 56 #neg: 56
Test set
Instances: 240 ; Features: 1048577 with an avg of 298 features per instance
--------------------------------------------------------------------------------
Test Estimate
             precision    recall  f1-score   support

         -1       0.74      0.75      0.74       120
          1       0.75      0.73      0.74       120

avg / total       0.74      0.74      0.74       240

APR: 0.779
ROC: 0.808
Cross-validated estimate
            accuracy: 0.812 +- 0.040
           precision: 0.848 +- 0.039
              recall: 0.767 +- 0.097
                  f1: 0.800 +- 0.055
   average_precision: 0.859 +- 0.037
             roc_auc: 0.857 +- 0.012
elapsed: 4.8 sec
--------------------------------------------------------------------------------
working on sample
training set sizes: #pos: 106 #neg: 106
Test set
Instances: 240 ; Features: 1048577 with an avg of 298 features per instance
--------------------------------------------------------------------------------
Test Estimate
             precision    recall  f1-score   support

         -1       0.72      0.68      0.70       120
          1       0.69      0.73      0.71       120

avg / total       0.70      0.70      0.70       240

APR: 0.788
ROC: 0.774
Cross-validated estimate
            accuracy: 0.808 +- 0.024
           precision: 0.834 +- 0.038
              recall: 0.775 +- 0.068
                  f1: 0.800 +- 0.032
   average_precision: 0.864 +- 0.014
             roc_auc: 0.867 +- 0.018
elapsed: 6.7 sec
--------------------------------------------------------------------------------
working on original+sample
training set sizes: #pos: 162 #neg: 162
Test set
Instances: 240 ; Features: 1048577 with an avg of 298 features per instance
--------------------------------------------------------------------------------
Test Estimate
             precision    recall  f1-score   support

         -1       0.72      0.78      0.75       120
          1       0.76      0.70      0.73       120

avg / total       0.74      0.74      0.74       240

APR: 0.795
ROC: 0.801
Cross-validated estimate
            accuracy: 0.808 +- 0.024
           precision: 0.834 +- 0.040
              recall: 0.775 +- 0.073
                  f1: 0.800 +- 0.033
   average_precision: 0.864 +- 0.019
             roc_auc: 0.866 +- 0.013
elapsed: 8.2 sec
Time elapsed: 29.9 sec
Positive
graph grammar stats:
#instances:56   #interfaces: 23   #cores: 25   #core-interface-pairs: 65
Negative
graph grammar stats:
#instances:56   #interfaces: 38   #cores: 33   #core-interface-pairs: 104
================================================================================
repetition: 7/10
training percentage:0.2
--------------------------------------------------------------------------------
working on original
training set sizes: #pos: 56 #neg: 56
Test set
Instances: 240 ; Features: 1048577 with an avg of 298 features per instance
--------------------------------------------------------------------------------
Test Estimate
             precision    recall  f1-score   support

         -1       0.72      0.81      0.76       120
          1       0.78      0.68      0.73       120

avg / total       0.75      0.75      0.74       240

APR: 0.782
ROC: 0.805
Cross-validated estimate
            accuracy: 0.804 +- 0.039
           precision: 0.851 +- 0.039
              recall: 0.742 +- 0.093
                  f1: 0.788 +- 0.054
   average_precision: 0.852 +- 0.020
             roc_auc: 0.852 +- 0.007
elapsed: 10.9 sec
--------------------------------------------------------------------------------
working on sample
training set sizes: #pos: 106 #neg: 106
Test set
Instances: 240 ; Features: 1048577 with an avg of 298 features per instance
--------------------------------------------------------------------------------
Test Estimate
             precision    recall  f1-score   support

         -1       0.71      0.63      0.67       120
          1       0.67      0.74      0.70       120

avg / total       0.69      0.69      0.69       240

APR: 0.757
ROC: 0.769
Cross-validated estimate
            accuracy: 0.787 +- 0.048
           precision: 0.817 +- 0.045
              recall: 0.742 +- 0.089
                  f1: 0.775 +- 0.062
   average_precision: 0.838 +- 0.056
             roc_auc: 0.854 +- 0.019
elapsed: 9.0 sec
--------------------------------------------------------------------------------
working on original+sample
training set sizes: #pos: 162 #neg: 162
Test set
Instances: 240 ; Features: 1048577 with an avg of 298 features per instance
--------------------------------------------------------------------------------
Test Estimate
             precision    recall  f1-score   support

         -1       0.74      0.75      0.74       120
          1       0.75      0.73      0.74       120

avg / total       0.74      0.74      0.74       240

APR: 0.770
ROC: 0.802
Cross-validated estimate
            accuracy: 0.808 +- 0.042
           precision: 0.835 +- 0.029
              recall: 0.767 +- 0.073
                  f1: 0.798 +- 0.053
   average_precision: 0.854 +- 0.041
             roc_auc: 0.867 +- 0.013
elapsed: 9.3 sec
Time elapsed: 44.9 sec
Positive
graph grammar stats:
#instances:56   #interfaces: 23   #cores: 25   #core-interface-pairs: 65
Negative
graph grammar stats:
#instances:56   #interfaces: 38   #cores: 33   #core-interface-pairs: 104
================================================================================
repetition: 8/10
training percentage:0.2
--------------------------------------------------------------------------------
working on original
training set sizes: #pos: 56 #neg: 56
Test set
Instances: 240 ; Features: 1048577 with an avg of 298 features per instance
--------------------------------------------------------------------------------
Test Estimate
             precision    recall  f1-score   support

         -1       0.73      0.82      0.77       120
          1       0.79      0.70      0.74       120

avg / total       0.76      0.76      0.76       240

APR: 0.814
ROC: 0.826
Cross-validated estimate
            accuracy: 0.808 +- 0.031
           precision: 0.850 +- 0.026
              recall: 0.750 +- 0.075
                  f1: 0.795 +- 0.043
   average_precision: 0.885 +- 0.009
             roc_auc: 0.878 +- 0.016
elapsed: 4.8 sec
--------------------------------------------------------------------------------
working on sample
training set sizes: #pos: 106 #neg: 105
Test set
Instances: 240 ; Features: 1048577 with an avg of 298 features per instance
--------------------------------------------------------------------------------
Test Estimate
             precision    recall  f1-score   support

         -1       0.68      0.67      0.67       120
          1       0.67      0.68      0.68       120

avg / total       0.68      0.68      0.67       240

APR: 0.766
ROC: 0.758
Cross-validated estimate
            accuracy: 0.779 +- 0.063
           precision: 0.806 +- 0.066
              recall: 0.733 +- 0.082
                  f1: 0.767 +- 0.071
   average_precision: 0.856 +- 0.023
             roc_auc: 0.860 +- 0.010
elapsed: 5.4 sec
--------------------------------------------------------------------------------
working on original+sample
training set sizes: #pos: 162 #neg: 161
Test set
Instances: 240 ; Features: 1048577 with an avg of 298 features per instance
--------------------------------------------------------------------------------
Test Estimate
             precision    recall  f1-score   support

         -1       0.72      0.74      0.73       120
          1       0.74      0.72      0.73       120

avg / total       0.73      0.73      0.73       240

APR: 0.776
ROC: 0.799
Cross-validated estimate
            accuracy: 0.812 +- 0.013
           precision: 0.864 +- 0.045
              recall: 0.750 +- 0.075
                  f1: 0.798 +- 0.028
   average_precision: 0.861 +- 0.025
             roc_auc: 0.859 +- 0.008
elapsed: 5.9 sec
Time elapsed: 23.9 sec
Positive
graph grammar stats:
#instances:56   #interfaces: 23   #cores: 25   #core-interface-pairs: 65
Negative
graph grammar stats:
#instances:56   #interfaces: 38   #cores: 33   #core-interface-pairs: 104
================================================================================
repetition: 9/10
training percentage:0.2
--------------------------------------------------------------------------------
working on original
training set sizes: #pos: 56 #neg: 56
Test set
Instances: 240 ; Features: 1048577 with an avg of 298 features per instance
--------------------------------------------------------------------------------
Test Estimate
             precision    recall  f1-score   support

         -1       0.74      0.80      0.77       120
          1       0.78      0.72      0.75       120

avg / total       0.76      0.76      0.76       240

APR: 0.802
ROC: 0.819
Cross-validated estimate
            accuracy: 0.787 +- 0.036
           precision: 0.831 +- 0.031
              recall: 0.725 +- 0.094
                  f1: 0.770 +- 0.056
   average_precision: 0.854 +- 0.033
             roc_auc: 0.859 +- 0.011
elapsed: 4.7 sec
--------------------------------------------------------------------------------
working on sample
training set sizes: #pos: 106 #neg: 105
Test set
Instances: 240 ; Features: 1048577 with an avg of 298 features per instance
--------------------------------------------------------------------------------
Test Estimate
             precision    recall  f1-score   support

         -1       0.73      0.72      0.73       120
          1       0.73      0.73      0.73       120

avg / total       0.73      0.73      0.73       240

APR: 0.785
ROC: 0.791
Cross-validated estimate
            accuracy: 0.817 +- 0.028
           precision: 0.848 +- 0.052
              recall: 0.783 +- 0.103
                  f1: 0.807 +- 0.047
   average_precision: 0.852 +- 0.036
             roc_auc: 0.860 +- 0.010
elapsed: 5.4 sec
--------------------------------------------------------------------------------
working on original+sample
training set sizes: #pos: 162 #neg: 161
Test set
Instances: 240 ; Features: 1048577 with an avg of 298 features per instance
--------------------------------------------------------------------------------
Test Estimate
             precision    recall  f1-score   support

         -1       0.75      0.80      0.77       120
          1       0.79      0.73      0.76       120

avg / total       0.77      0.77      0.77       240

APR: 0.803
ROC: 0.809
Cross-validated estimate
            accuracy: 0.812 +- 0.053
           precision: 0.844 +- 0.037
              recall: 0.767 +- 0.114
                  f1: 0.799 +- 0.070
   average_precision: 0.863 +- 0.029
             roc_auc: 0.867 +- 0.009
elapsed: 6.2 sec
Time elapsed: 24.6 sec
Positive
graph grammar stats:
#instances:56   #interfaces: 23   #cores: 25   #core-interface-pairs: 65
Negative
graph grammar stats:
#instances:56   #interfaces: 38   #cores: 33   #core-interface-pairs: 104
================================================================================
repetition: 10/10
training percentage:0.2
--------------------------------------------------------------------------------
working on original
training set sizes: #pos: 56 #neg: 56
Test set
Instances: 240 ; Features: 1048577 with an avg of 298 features per instance
--------------------------------------------------------------------------------
Test Estimate
             precision    recall  f1-score   support

         -1       0.75      0.81      0.78       120
          1       0.79      0.72      0.76       120

avg / total       0.77      0.77      0.77       240

APR: 0.798
ROC: 0.821
Cross-validated estimate
            accuracy: 0.804 +- 0.034
           precision: 0.844 +- 0.043
              recall: 0.750 +- 0.075
                  f1: 0.791 +- 0.043
   average_precision: 0.852 +- 0.049
             roc_auc: 0.864 +- 0.019
elapsed: 4.7 sec
--------------------------------------------------------------------------------
working on sample
training set sizes: #pos: 106 #neg: 105
Test set
Instances: 240 ; Features: 1048577 with an avg of 298 features per instance
--------------------------------------------------------------------------------
Test Estimate
             precision    recall  f1-score   support

         -1       0.70      0.72      0.71       120
          1       0.71      0.68      0.70       120

avg / total       0.70      0.70      0.70       240

APR: 0.746
ROC: 0.773
Cross-validated estimate
            accuracy: 0.812 +- 0.023
           precision: 0.840 +- 0.049
              recall: 0.783 +- 0.100
                  f1: 0.803 +- 0.043
   average_precision: 0.870 +- 0.023
             roc_auc: 0.873 +- 0.021
elapsed: 5.6 sec
--------------------------------------------------------------------------------
working on original+sample
training set sizes: #pos: 162 #neg: 161
Test set
Instances: 240 ; Features: 1048577 with an avg of 298 features per instance
--------------------------------------------------------------------------------
Test Estimate
             precision    recall  f1-score   support

         -1       0.71      0.78      0.75       120
          1       0.76      0.68      0.72       120

avg / total       0.74      0.73      0.73       240

APR: 0.803
ROC: 0.809
Cross-validated estimate
            accuracy: 0.808 +- 0.042
           precision: 0.832 +- 0.033
              recall: 0.775 +- 0.101
                  f1: 0.798 +- 0.059
   average_precision: 0.861 +- 0.015
             roc_auc: 0.865 +- 0.008
elapsed: 6.3 sec
Time elapsed: 24.8 sec
Positive
graph grammar stats:
#instances:112   #interfaces: 44   #cores: 31   #core-interface-pairs: 136
Negative
graph grammar stats:
#instances:112   #interfaces: 72   #cores: 42   #core-interface-pairs: 216
================================================================================
repetition: 1/10
training percentage:0.4
--------------------------------------------------------------------------------
working on original
training set sizes: #pos: 112 #neg: 112
Test set
Instances: 240 ; Features: 1048577 with an avg of 298 features per instance
--------------------------------------------------------------------------------
Test Estimate
             precision    recall  f1-score   support

         -1       0.75      0.84      0.79       120
          1       0.82      0.72      0.76       120

avg / total       0.78      0.78      0.78       240

APR: 0.827
ROC: 0.843
Cross-validated estimate
            accuracy: 0.808 +- 0.036
           precision: 0.846 +- 0.027
              recall: 0.758 +- 0.100
                  f1: 0.795 +- 0.054
   average_precision: 0.854 +- 0.032
             roc_auc: 0.861 +- 0.013
elapsed: 5.5 sec
--------------------------------------------------------------------------------
working on sample
training set sizes: #pos: 218 #neg: 216
Test set
Instances: 240 ; Features: 1048577 with an avg of 298 features per instance
--------------------------------------------------------------------------------
Test Estimate
             precision    recall  f1-score   support

         -1       0.83      0.67      0.74       120
          1       0.72      0.87      0.79       120

avg / total       0.78      0.77      0.76       240

APR: 0.817
ROC: 0.825
Cross-validated estimate
            accuracy: 0.812 +- 0.035
           precision: 0.840 +- 0.035
              recall: 0.775 +- 0.077
                  f1: 0.803 +- 0.046
   average_precision: 0.856 +- 0.038
             roc_auc: 0.869 +- 0.012
elapsed: 9.1 sec
--------------------------------------------------------------------------------
working on original+sample
training set sizes: #pos: 330 #neg: 328
Test set
Instances: 240 ; Features: 1048577 with an avg of 298 features per instance
--------------------------------------------------------------------------------
Test Estimate
             precision    recall  f1-score   support

         -1       0.81      0.78      0.80       120
          1       0.79      0.82      0.80       120

avg / total       0.80      0.80      0.80       240

APR: 0.829
ROC: 0.838
Cross-validated estimate
            accuracy: 0.787 +- 0.061
           precision: 0.833 +- 0.038
              recall: 0.717 +- 0.122
                  f1: 0.766 +- 0.086
   average_precision: 0.856 +- 0.025
             roc_auc: 0.861 +- 0.007
elapsed: 8.5 sec
Time elapsed: 40.1 sec
Positive
graph grammar stats:
#instances:112   #interfaces: 44   #cores: 31   #core-interface-pairs: 136
Negative
graph grammar stats:
#instances:112   #interfaces: 72   #cores: 42   #core-interface-pairs: 216
================================================================================
repetition: 2/10
training percentage:0.4
--------------------------------------------------------------------------------
working on original
training set sizes: #pos: 112 #neg: 112
Test set
Instances: 240 ; Features: 1048577 with an avg of 298 features per instance
--------------------------------------------------------------------------------
Test Estimate
             precision    recall  f1-score   support

         -1       0.73      0.86      0.79       120
          1       0.83      0.68      0.75       120

avg / total       0.78      0.77      0.77       240

APR: 0.846
ROC: 0.851
Cross-validated estimate
            accuracy: 0.787 +- 0.028
           precision: 0.834 +- 0.049
              recall: 0.725 +- 0.073
                  f1: 0.772 +- 0.039
   average_precision: 0.863 +- 0.025
             roc_auc: 0.859 +- 0.006
elapsed: 5.6 sec
--------------------------------------------------------------------------------
working on sample
training set sizes: #pos: 218 #neg: 216
Test set
Instances: 240 ; Features: 1048577 with an avg of 298 features per instance
--------------------------------------------------------------------------------
Test Estimate
             precision    recall  f1-score   support

         -1       0.78      0.76      0.77       120
          1       0.76      0.78      0.77       120

avg / total       0.77      0.77      0.77       240

APR: 0.818
ROC: 0.824
Cross-validated estimate
            accuracy: 0.817 +- 0.033
           precision: 0.855 +- 0.041
              recall: 0.767 +- 0.073
                  f1: 0.805 +- 0.043
   average_precision: 0.867 +- 0.028
             roc_auc: 0.866 +- 0.010
elapsed: 9.4 sec
--------------------------------------------------------------------------------
working on original+sample
training set sizes: #pos: 330 #neg: 328
Test set
Instances: 240 ; Features: 1048577 with an avg of 298 features per instance
--------------------------------------------------------------------------------
Test Estimate
             precision    recall  f1-score   support

         -1       0.77      0.80      0.79       120
          1       0.79      0.77      0.78       120

avg / total       0.78      0.78      0.78       240

APR: 0.844
ROC: 0.849
Cross-validated estimate
            accuracy: 0.817 +- 0.016
           precision: 0.848 +- 0.025
              recall: 0.775 +- 0.057
                  f1: 0.808 +- 0.025
   average_precision: 0.859 +- 0.048
             roc_auc: 0.868 +- 0.013
elapsed: 8.6 sec
Time elapsed: 39.3 sec
Positive
graph grammar stats:
#instances:112   #interfaces: 44   #cores: 31   #core-interface-pairs: 136
Negative
graph grammar stats:
#instances:112   #interfaces: 72   #cores: 42   #core-interface-pairs: 216
================================================================================
repetition: 3/10
training percentage:0.4
--------------------------------------------------------------------------------
working on original
training set sizes: #pos: 112 #neg: 112
Test set
Instances: 240 ; Features: 1048577 with an avg of 298 features per instance
--------------------------------------------------------------------------------
Test Estimate
             precision    recall  f1-score   support

         -1       0.76      0.87      0.81       120
          1       0.85      0.73      0.79       120

avg / total       0.81      0.80      0.80       240

APR: 0.843
ROC: 0.852
Cross-validated estimate
            accuracy: 0.808 +- 0.024
           precision: 0.839 +- 0.031
              recall: 0.767 +- 0.073
                  f1: 0.798 +- 0.036
   average_precision: 0.865 +- 0.016
             roc_auc: 0.865 +- 0.008
elapsed: 5.7 sec
--------------------------------------------------------------------------------
working on sample
training set sizes: #pos: 218 #neg: 216
Test set
Instances: 240 ; Features: 1048577 with an avg of 298 features per instance
--------------------------------------------------------------------------------
Test Estimate
             precision    recall  f1-score   support

         -1       0.78      0.68      0.72       120
          1       0.71      0.81      0.76       120

avg / total       0.75      0.74      0.74       240

APR: 0.819
ROC: 0.817
Cross-validated estimate
            accuracy: 0.808 +- 0.040
           precision: 0.845 +- 0.017
              recall: 0.758 +- 0.110
                  f1: 0.794 +- 0.064
   average_precision: 0.857 +- 0.038
             roc_auc: 0.864 +- 0.014
elapsed: 7.8 sec
--------------------------------------------------------------------------------
working on original+sample
training set sizes: #pos: 330 #neg: 328
Test set
Instances: 240 ; Features: 1048577 with an avg of 298 features per instance
--------------------------------------------------------------------------------
Test Estimate
             precision    recall  f1-score   support

         -1       0.78      0.76      0.77       120
          1       0.76      0.78      0.77       120

avg / total       0.77      0.77      0.77       240

APR: 0.818
ROC: 0.830
Cross-validated estimate
            accuracy: 0.800 +- 0.028
           precision: 0.842 +- 0.021
              recall: 0.742 +- 0.085
                  f1: 0.785 +- 0.045
   average_precision: 0.859 +- 0.021
             roc_auc: 0.861 +- 0.006
elapsed: 8.7 sec
Time elapsed: 37.2 sec
Positive
graph grammar stats:
#instances:112   #interfaces: 44   #cores: 31   #core-interface-pairs: 136
Negative
graph grammar stats:
#instances:112   #interfaces: 72   #cores: 42   #core-interface-pairs: 216
================================================================================
repetition: 4/10
training percentage:0.4
--------------------------------------------------------------------------------
working on original
training set sizes: #pos: 112 #neg: 112
Test set
Instances: 240 ; Features: 1048577 with an avg of 298 features per instance
--------------------------------------------------------------------------------
Test Estimate
             precision    recall  f1-score   support

         -1       0.76      0.83      0.79       120
          1       0.81      0.73      0.77       120

avg / total       0.79      0.78      0.78       240

APR: 0.823
ROC: 0.833
Cross-validated estimate
            accuracy: 0.796 +- 0.031
           precision: 0.833 +- 0.025
              recall: 0.742 +- 0.072
                  f1: 0.782 +- 0.042
   average_precision: 0.857 +- 0.029
             roc_auc: 0.860 +- 0.009
elapsed: 5.2 sec
--------------------------------------------------------------------------------
working on sample
training set sizes: #pos: 218 #neg: 216
Test set
Instances: 240 ; Features: 1048577 with an avg of 298 features per instance
--------------------------------------------------------------------------------
Test Estimate
             precision    recall  f1-score   support

         -1       0.81      0.62      0.70       120
          1       0.69      0.85      0.76       120

avg / total       0.75      0.74      0.73       240

APR: 0.839
ROC: 0.837
Cross-validated estimate
            accuracy: 0.804 +- 0.039
           precision: 0.846 +- 0.050
              recall: 0.750 +- 0.083
                  f1: 0.791 +- 0.051
   average_precision: 0.839 +- 0.043
             roc_auc: 0.856 +- 0.010
elapsed: 7.9 sec
--------------------------------------------------------------------------------
working on original+sample
training set sizes: #pos: 330 #neg: 328
Test set
Instances: 240 ; Features: 1048577 with an avg of 298 features per instance
--------------------------------------------------------------------------------
Test Estimate
             precision    recall  f1-score   support

         -1       0.80      0.82      0.81       120
          1       0.81      0.80      0.81       120

avg / total       0.81      0.81      0.81       240

APR: 0.838
ROC: 0.854
Cross-validated estimate
            accuracy: 0.796 +- 0.033
           precision: 0.826 +- 0.026
              recall: 0.750 +- 0.070
                  f1: 0.784 +- 0.043
   average_precision: 0.856 +- 0.016
             roc_auc: 0.854 +- 0.006
elapsed: 8.0 sec
Time elapsed: 36.8 sec
Positive
graph grammar stats:
#instances:112   #interfaces: 44   #cores: 31   #core-interface-pairs: 136
Negative
graph grammar stats:
#instances:112   #interfaces: 72   #cores: 42   #core-interface-pairs: 216
================================================================================
repetition: 5/10
training percentage:0.4
--------------------------------------------------------------------------------
working on original
training set sizes: #pos: 112 #neg: 112
Test set
Instances: 240 ; Features: 1048577 with an avg of 298 features per instance
--------------------------------------------------------------------------------
Test Estimate
             precision    recall  f1-score   support

         -1       0.77      0.82      0.80       120
          1       0.81      0.75      0.78       120

avg / total       0.79      0.79      0.79       240

APR: 0.829
ROC: 0.840
Cross-validated estimate
            accuracy: 0.787 +- 0.024
           precision: 0.831 +- 0.037
              recall: 0.725 +- 0.057
                  f1: 0.772 +- 0.031
   average_precision: 0.861 +- 0.015
             roc_auc: 0.867 +- 0.012
elapsed: 5.8 sec
--------------------------------------------------------------------------------
working on sample
training set sizes: #pos: 218 #neg: 216
Test set
Instances: 240 ; Features: 1048577 with an avg of 298 features per instance
--------------------------------------------------------------------------------
Test Estimate
             precision    recall  f1-score   support

         -1       0.79      0.71      0.75       120
          1       0.73      0.81      0.77       120

avg / total       0.76      0.76      0.76       240

APR: 0.816
ROC: 0.824
Cross-validated estimate
            accuracy: 0.775 +- 0.055
           precision: 0.803 +- 0.035
              recall: 0.725 +- 0.117
                  f1: 0.758 +- 0.080
   average_precision: 0.856 +- 0.039
             roc_auc: 0.866 +- 0.015
elapsed: 7.6 sec
--------------------------------------------------------------------------------
working on original+sample
training set sizes: #pos: 330 #neg: 328
Test set
Instances: 240 ; Features: 1048577 with an avg of 298 features per instance
--------------------------------------------------------------------------------
Test Estimate
             precision    recall  f1-score   support

         -1       0.79      0.79      0.79       120
          1       0.79      0.79      0.79       120

avg / total       0.79      0.79      0.79       240

APR: 0.840
ROC: 0.853
Cross-validated estimate
            accuracy: 0.808 +- 0.031
           precision: 0.858 +- 0.029
              recall: 0.742 +- 0.081
                  f1: 0.792 +- 0.047
   average_precision: 0.852 +- 0.048
             roc_auc: 0.864 +- 0.012
elapsed: 8.2 sec
Time elapsed: 37.8 sec
Positive
graph grammar stats:
#instances:112   #interfaces: 44   #cores: 31   #core-interface-pairs: 136
Negative
graph grammar stats:
#instances:112   #interfaces: 72   #cores: 42   #core-interface-pairs: 216
================================================================================
repetition: 6/10
training percentage:0.4
--------------------------------------------------------------------------------
working on original
training set sizes: #pos: 112 #neg: 112
Test set
Instances: 240 ; Features: 1048577 with an avg of 298 features per instance
--------------------------------------------------------------------------------
Test Estimate
             precision    recall  f1-score   support

         -1       0.77      0.84      0.80       120
          1       0.82      0.74      0.78       120

avg / total       0.79      0.79      0.79       240

APR: 0.837
ROC: 0.846
Cross-validated estimate
            accuracy: 0.800 +- 0.043
           precision: 0.829 +- 0.039
              recall: 0.758 +- 0.096
                  f1: 0.788 +- 0.058
   average_precision: 0.859 +- 0.021
             roc_auc: 0.854 +- 0.011
elapsed: 5.7 sec
--------------------------------------------------------------------------------
working on sample
training set sizes: #pos: 218 #neg: 216
Test set
Instances: 240 ; Features: 1048577 with an avg of 298 features per instance
--------------------------------------------------------------------------------
Test Estimate
             precision    recall  f1-score   support

         -1       0.77      0.73      0.75       120
          1       0.75      0.78      0.76       120

avg / total       0.76      0.76      0.76       240

APR: 0.814
ROC: 0.822
Cross-validated estimate
            accuracy: 0.812 +- 0.044
           precision: 0.851 +- 0.030
              recall: 0.758 +- 0.093
                  f1: 0.799 +- 0.060
   average_precision: 0.858 +- 0.009
             roc_auc: 0.858 +- 0.011
elapsed: 7.8 sec
--------------------------------------------------------------------------------
working on original+sample
training set sizes: #pos: 330 #neg: 328
Test set
Instances: 240 ; Features: 1048577 with an avg of 298 features per instance
--------------------------------------------------------------------------------
Test Estimate
             precision    recall  f1-score   support

         -1       0.79      0.81      0.80       120
          1       0.80      0.78      0.79       120

avg / total       0.80      0.80      0.80       240

APR: 0.833
ROC: 0.842
Cross-validated estimate
            accuracy: 0.817 +- 0.040
           precision: 0.854 +- 0.031
              recall: 0.767 +- 0.101
                  f1: 0.804 +- 0.058
   average_precision: 0.860 +- 0.037
             roc_auc: 0.870 +- 0.005
elapsed: 8.9 sec
Time elapsed: 38.1 sec
Positive
graph grammar stats:
#instances:112   #interfaces: 44   #cores: 31   #core-interface-pairs: 136
Negative
graph grammar stats:
#instances:112   #interfaces: 72   #cores: 42   #core-interface-pairs: 216
================================================================================
repetition: 7/10
training percentage:0.4
--------------------------------------------------------------------------------
working on original
training set sizes: #pos: 112 #neg: 112
Test set
Instances: 240 ; Features: 1048577 with an avg of 298 features per instance
--------------------------------------------------------------------------------
Test Estimate
             precision    recall  f1-score   support

         -1       0.76      0.87      0.81       120
          1       0.84      0.72      0.78       120

avg / total       0.80      0.80      0.79       240

APR: 0.829
ROC: 0.850
Cross-validated estimate
            accuracy: 0.796 +- 0.048
           precision: 0.840 +- 0.056
              recall: 0.733 +- 0.082
                  f1: 0.780 +- 0.060
   average_precision: 0.854 +- 0.021
             roc_auc: 0.852 +- 0.014
elapsed: 5.5 sec
--------------------------------------------------------------------------------
working on sample
training set sizes: #pos: 218 #neg: 216
Test set
Instances: 240 ; Features: 1048577 with an avg of 298 features per instance
--------------------------------------------------------------------------------
Test Estimate
             precision    recall  f1-score   support

         -1       0.75      0.72      0.74       120
          1       0.73      0.76      0.75       120

avg / total       0.74      0.74      0.74       240

APR: 0.766
ROC: 0.790
Cross-validated estimate
            accuracy: 0.817 +- 0.028
           precision: 0.859 +- 0.045
              recall: 0.767 +- 0.094
                  f1: 0.804 +- 0.045
   average_precision: 0.863 +- 0.017
             roc_auc: 0.868 +- 0.008
elapsed: 7.8 sec
--------------------------------------------------------------------------------
working on original+sample
training set sizes: #pos: 330 #neg: 328
Test set
Instances: 240 ; Features: 1048577 with an avg of 298 features per instance
--------------------------------------------------------------------------------
Test Estimate
             precision    recall  f1-score   support

         -1       0.82      0.75      0.78       120
          1       0.77      0.83      0.80       120

avg / total       0.79      0.79      0.79       240

APR: 0.835
ROC: 0.842
Cross-validated estimate
            accuracy: 0.775 +- 0.016
           precision: 0.815 +- 0.034
              recall: 0.717 +- 0.067
                  f1: 0.760 +- 0.028
   average_precision: 0.854 +- 0.037
             roc_auc: 0.867 +- 0.017
elapsed: 8.4 sec
Time elapsed: 37.3 sec
Positive
graph grammar stats:
#instances:112   #interfaces: 44   #cores: 31   #core-interface-pairs: 136
Negative
graph grammar stats:
#instances:112   #interfaces: 72   #cores: 42   #core-interface-pairs: 216
================================================================================
repetition: 8/10
training percentage:0.4
--------------------------------------------------------------------------------
working on original
training set sizes: #pos: 112 #neg: 112
Test set
Instances: 240 ; Features: 1048577 with an avg of 298 features per instance
--------------------------------------------------------------------------------
Test Estimate
             precision    recall  f1-score   support

         -1       0.76      0.86      0.81       120
          1       0.84      0.73      0.78       120

avg / total       0.80      0.80      0.80       240

APR: 0.834
ROC: 0.844
Cross-validated estimate
            accuracy: 0.796 +- 0.036
           precision: 0.829 +- 0.022
              recall: 0.750 +- 0.109
                  f1: 0.781 +- 0.060
   average_precision: 0.842 +- 0.032
             roc_auc: 0.856 +- 0.009
elapsed: 5.6 sec
--------------------------------------------------------------------------------
working on sample
training set sizes: #pos: 218 #neg: 216
Test set
Instances: 240 ; Features: 1048577 with an avg of 298 features per instance
--------------------------------------------------------------------------------
Test Estimate
             precision    recall  f1-score   support

         -1       0.79      0.66      0.72       120
          1       0.71      0.82      0.76       120

avg / total       0.75      0.74      0.74       240

APR: 0.812
ROC: 0.824
Cross-validated estimate
            accuracy: 0.796 +- 0.036
           precision: 0.827 +- 0.057
              recall: 0.758 +- 0.089
                  f1: 0.786 +- 0.048
   average_precision: 0.853 +- 0.020
             roc_auc: 0.855 +- 0.009
elapsed: 7.9 sec
--------------------------------------------------------------------------------
working on original+sample
training set sizes: #pos: 330 #neg: 328
Test set
Instances: 240 ; Features: 1048577 with an avg of 298 features per instance
--------------------------------------------------------------------------------
Test Estimate
             precision    recall  f1-score   support

         -1       0.80      0.78      0.79       120
          1       0.78      0.81      0.80       120

avg / total       0.79      0.79      0.79       240

APR: 0.832
ROC: 0.856
Cross-validated estimate
            accuracy: 0.812 +- 0.037
           precision: 0.853 +- 0.041
              recall: 0.758 +- 0.081
                  f1: 0.800 +- 0.048
   average_precision: 0.875 +- 0.021
             roc_auc: 0.873 +- 0.010
elapsed: 8.4 sec
Time elapsed: 37.4 sec
Positive
graph grammar stats:
#instances:112   #interfaces: 44   #cores: 31   #core-interface-pairs: 136
Negative
graph grammar stats:
#instances:112   #interfaces: 72   #cores: 42   #core-interface-pairs: 216
================================================================================
repetition: 9/10
training percentage:0.4
--------------------------------------------------------------------------------
working on original
training set sizes: #pos: 112 #neg: 112
Test set
Instances: 240 ; Features: 1048577 with an avg of 298 features per instance
--------------------------------------------------------------------------------
Test Estimate
             precision    recall  f1-score   support

         -1       0.74      0.84      0.79       120
          1       0.82      0.70      0.75       120

avg / total       0.78      0.77      0.77       240

APR: 0.817
ROC: 0.825
Cross-validated estimate
            accuracy: 0.808 +- 0.040
           precision: 0.844 +- 0.040
              recall: 0.758 +- 0.072
                  f1: 0.797 +- 0.049
   average_precision: 0.864 +- 0.045
             roc_auc: 0.870 +- 0.012
elapsed: 5.6 sec
--------------------------------------------------------------------------------
working on sample
training set sizes: #pos: 218 #neg: 216
Test set
Instances: 240 ; Features: 1048577 with an avg of 298 features per instance
--------------------------------------------------------------------------------
Test Estimate
             precision    recall  f1-score   support

         -1       0.77      0.66      0.71       120
          1       0.70      0.81      0.75       120

avg / total       0.74      0.73      0.73       240

APR: 0.817
ROC: 0.808
Cross-validated estimate
            accuracy: 0.800 +- 0.028
           precision: 0.832 +- 0.034
              recall: 0.758 +- 0.100
                  f1: 0.788 +- 0.047
   average_precision: 0.855 +- 0.037
             roc_auc: 0.853 +- 0.012
elapsed: 7.9 sec
--------------------------------------------------------------------------------
working on original+sample
training set sizes: #pos: 330 #neg: 328
Test set
Instances: 240 ; Features: 1048577 with an avg of 298 features per instance
--------------------------------------------------------------------------------
Test Estimate
             precision    recall  f1-score   support

         -1       0.80      0.82      0.81       120
          1       0.81      0.79      0.80       120

avg / total       0.80      0.80      0.80       240

APR: 0.842
ROC: 0.857
Cross-validated estimate
            accuracy: 0.804 +- 0.039
           precision: 0.843 +- 0.035
              recall: 0.750 +- 0.087
                  f1: 0.790 +- 0.054
   average_precision: 0.868 +- 0.021
             roc_auc: 0.870 +- 0.008
elapsed: 8.1 sec
Time elapsed: 36.6 sec
Positive
graph grammar stats:
#instances:112   #interfaces: 44   #cores: 31   #core-interface-pairs: 136
Negative
graph grammar stats:
#instances:112   #interfaces: 72   #cores: 42   #core-interface-pairs: 216
================================================================================
repetition: 10/10
training percentage:0.4
--------------------------------------------------------------------------------
working on original
training set sizes: #pos: 112 #neg: 112
Test set
Instances: 240 ; Features: 1048577 with an avg of 298 features per instance
--------------------------------------------------------------------------------
Test Estimate
             precision    recall  f1-score   support

         -1       0.77      0.86      0.81       120
          1       0.84      0.74      0.79       120

avg / total       0.80      0.80      0.80       240

APR: 0.815
ROC: 0.830
Cross-validated estimate
            accuracy: 0.808 +- 0.036
           precision: 0.851 +- 0.033
              recall: 0.750 +- 0.087
                  f1: 0.794 +- 0.052
   average_precision: 0.863 +- 0.005
             roc_auc: 0.863 +- 0.018
elapsed: 5.5 sec
--------------------------------------------------------------------------------
working on sample
training set sizes: #pos: 218 #neg: 216
Test set
Instances: 240 ; Features: 1048577 with an avg of 298 features per instance
--------------------------------------------------------------------------------
Test Estimate
             precision    recall  f1-score   support

         -1       0.76      0.59      0.67       120
          1       0.67      0.82      0.73       120

avg / total       0.72      0.70      0.70       240

APR: 0.794
ROC: 0.790
Cross-validated estimate
            accuracy: 0.796 +- 0.020
           precision: 0.824 +- 0.038
              recall: 0.758 +- 0.076
                  f1: 0.786 +- 0.033
   average_precision: 0.847 +- 0.048
             roc_auc: 0.863 +- 0.006
elapsed: 8.2 sec
--------------------------------------------------------------------------------
working on original+sample
training set sizes: #pos: 330 #neg: 328
Test set
Instances: 240 ; Features: 1048577 with an avg of 298 features per instance
--------------------------------------------------------------------------------
Test Estimate
             precision    recall  f1-score   support

         -1       0.79      0.78      0.78       120
          1       0.78      0.80      0.79       120

avg / total       0.79      0.79      0.79       240

APR: 0.812
ROC: 0.830
Cross-validated estimate
            accuracy: 0.800 +- 0.028
           precision: 0.839 +- 0.038
              recall: 0.750 +- 0.102
                  f1: 0.786 +- 0.047
   average_precision: 0.850 +- 0.044
             roc_auc: 0.859 +- 0.010
elapsed: 8.2 sec
Time elapsed: 36.9 sec
Positive
graph grammar stats:
#instances:168   #interfaces: 71   #cores: 40   #core-interface-pairs: 213
Negative
graph grammar stats:
#instances:168   #interfaces: 97   #cores: 47   #core-interface-pairs: 310
================================================================================
repetition: 1/10
training percentage:0.6
--------------------------------------------------------------------------------
working on original
training set sizes: #pos: 168 #neg: 168
Test set
Instances: 240 ; Features: 1048577 with an avg of 298 features per instance
--------------------------------------------------------------------------------
Test Estimate
             precision    recall  f1-score   support

         -1       0.79      0.83      0.81       120
          1       0.82      0.78      0.80       120

avg / total       0.81      0.80      0.80       240

APR: 0.845
ROC: 0.855
Cross-validated estimate
            accuracy: 0.787 +- 0.036
           precision: 0.820 +- 0.043
              recall: 0.742 +- 0.096
                  f1: 0.774 +- 0.052
   average_precision: 0.854 +- 0.022
             roc_auc: 0.853 +- 0.009
elapsed: 6.1 sec
--------------------------------------------------------------------------------
working on sample
training set sizes: #pos: 328 #neg: 320
Test set
Instances: 240 ; Features: 1048577 with an avg of 298 features per instance
--------------------------------------------------------------------------------
Test Estimate
             precision    recall  f1-score   support

         -1       0.82      0.64      0.72       120
          1       0.71      0.86      0.77       120

avg / total       0.76      0.75      0.75       240

APR: 0.836
ROC: 0.843
Cross-validated estimate
            accuracy: 0.804 +- 0.039
           precision: 0.838 +- 0.026
              recall: 0.758 +- 0.110
                  f1: 0.791 +- 0.057
   average_precision: 0.856 +- 0.036
             roc_auc: 0.862 +- 0.006
elapsed: 8.3 sec
--------------------------------------------------------------------------------
working on original+sample
training set sizes: #pos: 496 #neg: 488
Test set
Instances: 240 ; Features: 1048577 with an avg of 298 features per instance
--------------------------------------------------------------------------------
Test Estimate
             precision    recall  f1-score   support

         -1       0.79      0.78      0.79       120
          1       0.79      0.79      0.79       120

avg / total       0.79      0.79      0.79       240

APR: 0.849
ROC: 0.854
Cross-validated estimate
            accuracy: 0.817 +- 0.024
           precision: 0.855 +- 0.053
              recall: 0.775 +- 0.104
                  f1: 0.805 +- 0.045
   average_precision: 0.862 +- 0.021
             roc_auc: 0.864 +- 0.009
elapsed: 9.9 sec
Time elapsed: 44.6 sec
Positive
graph grammar stats:
#instances:168   #interfaces: 71   #cores: 40   #core-interface-pairs: 213
Negative
graph grammar stats:
#instances:168   #interfaces: 97   #cores: 47   #core-interface-pairs: 310
================================================================================
repetition: 2/10
training percentage:0.6
--------------------------------------------------------------------------------
working on original
training set sizes: #pos: 168 #neg: 168
Test set
Instances: 240 ; Features: 1048577 with an avg of 298 features per instance
--------------------------------------------------------------------------------
Test Estimate
             precision    recall  f1-score   support

         -1       0.78      0.83      0.81       120
          1       0.82      0.77      0.79       120

avg / total       0.80      0.80      0.80       240

APR: 0.849
ROC: 0.854
Cross-validated estimate
            accuracy: 0.825 +- 0.025
           precision: 0.863 +- 0.032
              recall: 0.775 +- 0.057
                  f1: 0.815 +- 0.032
   average_precision: 0.856 +- 0.038
             roc_auc: 0.865 +- 0.010
elapsed: 6.4 sec
--------------------------------------------------------------------------------
working on sample
training set sizes: #pos: 328 #neg: 320
Test set
Instances: 240 ; Features: 1048577 with an avg of 298 features per instance
--------------------------------------------------------------------------------
Test Estimate
             precision    recall  f1-score   support

         -1       0.80      0.61      0.69       120
          1       0.68      0.85      0.76       120

avg / total       0.74      0.73      0.73       240

APR: 0.831
ROC: 0.828
Cross-validated estimate
            accuracy: 0.821 +- 0.045
           precision: 0.862 +- 0.029
              recall: 0.767 +- 0.107
                  f1: 0.807 +- 0.062
   average_precision: 0.863 +- 0.025
             roc_auc: 0.866 +- 0.013
elapsed: 8.6 sec
--------------------------------------------------------------------------------
working on original+sample
training set sizes: #pos: 496 #neg: 488
Test set
Instances: 240 ; Features: 1048577 with an avg of 298 features per instance
--------------------------------------------------------------------------------
Test Estimate
             precision    recall  f1-score   support

         -1       0.83      0.76      0.79       120
          1       0.78      0.84      0.81       120

avg / total       0.80      0.80      0.80       240

APR: 0.859
ROC: 0.864
Cross-validated estimate
            accuracy: 0.804 +- 0.043
           precision: 0.841 +- 0.032
              recall: 0.750 +- 0.087
                  f1: 0.790 +- 0.058
   average_precision: 0.867 +- 0.017
             roc_auc: 0.871 +- 0.010
elapsed: 10.8 sec
Time elapsed: 47.0 sec
Positive
graph grammar stats:
#instances:168   #interfaces: 71   #cores: 40   #core-interface-pairs: 213
Negative
graph grammar stats:
#instances:168   #interfaces: 97   #cores: 47   #core-interface-pairs: 310
================================================================================
repetition: 3/10
training percentage:0.6
--------------------------------------------------------------------------------
working on original
training set sizes: #pos: 168 #neg: 168
Test set
Instances: 240 ; Features: 1048577 with an avg of 298 features per instance
--------------------------------------------------------------------------------
Test Estimate
             precision    recall  f1-score   support

         -1       0.78      0.86      0.82       120
          1       0.84      0.76      0.80       120

avg / total       0.81      0.81      0.81       240

APR: 0.858
ROC: 0.861
Cross-validated estimate
            accuracy: 0.800 +- 0.025
           precision: 0.853 +- 0.048
              recall: 0.733 +- 0.086
                  f1: 0.783 +- 0.041
   average_precision: 0.863 +- 0.017
             roc_auc: 0.864 +- 0.013
elapsed: 6.0 sec
--------------------------------------------------------------------------------
working on sample
training set sizes: #pos: 328 #neg: 320
Test set
Instances: 240 ; Features: 1048577 with an avg of 298 features per instance
--------------------------------------------------------------------------------
Test Estimate
             precision    recall  f1-score   support

         -1       0.82      0.65      0.73       120
          1       0.71      0.86      0.78       120

avg / total       0.77      0.75      0.75       240

APR: 0.854
ROC: 0.851
Cross-validated estimate
            accuracy: 0.812 +- 0.023
           precision: 0.832 +- 0.037
              recall: 0.792 +- 0.095
                  f1: 0.806 +- 0.039
   average_precision: 0.863 +- 0.031
             roc_auc: 0.867 +- 0.007
elapsed: 8.6 sec
--------------------------------------------------------------------------------
working on original+sample
training set sizes: #pos: 496 #neg: 488
Test set
Instances: 240 ; Features: 1048577 with an avg of 298 features per instance
--------------------------------------------------------------------------------
Test Estimate
             precision    recall  f1-score   support

         -1       0.82      0.82      0.82       120
          1       0.82      0.82      0.82       120

avg / total       0.82      0.82      0.82       240

APR: 0.857
ROC: 0.874
Cross-validated estimate
            accuracy: 0.800 +- 0.017
           precision: 0.837 +- 0.029
              recall: 0.750 +- 0.070
                  f1: 0.788 +- 0.030
   average_precision: 0.855 +- 0.039
             roc_auc: 0.866 +- 0.013
elapsed: 10.2 sec
Time elapsed: 45.0 sec
Positive
graph grammar stats:
#instances:168   #interfaces: 71   #cores: 40   #core-interface-pairs: 213
Negative
graph grammar stats:
#instances:168   #interfaces: 97   #cores: 47   #core-interface-pairs: 310
================================================================================
repetition: 4/10
training percentage:0.6
--------------------------------------------------------------------------------
working on original
training set sizes: #pos: 168 #neg: 168
Test set
Instances: 240 ; Features: 1048577 with an avg of 298 features per instance
--------------------------------------------------------------------------------
Test Estimate
             precision    recall  f1-score   support

         -1       0.77      0.88      0.82       120
          1       0.85      0.73      0.79       120

avg / total       0.81      0.80      0.80       240

APR: 0.848
ROC: 0.845
Cross-validated estimate
            accuracy: 0.812 +- 0.048
           precision: 0.853 +- 0.036
              recall: 0.758 +- 0.116
                  f1: 0.797 +- 0.070
   average_precision: 0.866 +- 0.022
             roc_auc: 0.863 +- 0.022
elapsed: 6.4 sec
--------------------------------------------------------------------------------
working on sample
training set sizes: #pos: 328 #neg: 320
Test set
Instances: 240 ; Features: 1048577 with an avg of 298 features per instance
--------------------------------------------------------------------------------
Test Estimate
             precision    recall  f1-score   support

         -1       0.82      0.57      0.67       120
          1       0.67      0.88      0.76       120

avg / total       0.74      0.72      0.71       240

APR: 0.829
ROC: 0.842
Cross-validated estimate
            accuracy: 0.825 +- 0.039
           precision: 0.857 +- 0.028
              recall: 0.783 +- 0.103
                  f1: 0.814 +- 0.057
   average_precision: 0.877 +- 0.013
             roc_auc: 0.876 +- 0.005
elapsed: 8.6 sec
--------------------------------------------------------------------------------
working on original+sample
training set sizes: #pos: 496 #neg: 488
Test set
Instances: 240 ; Features: 1048577 with an avg of 298 features per instance
--------------------------------------------------------------------------------
Test Estimate
             precision    recall  f1-score   support

         -1       0.81      0.80      0.80       120
          1       0.80      0.81      0.80       120

avg / total       0.80      0.80      0.80       240

APR: 0.855
ROC: 0.859
Cross-validated estimate
            accuracy: 0.825 +- 0.039
           precision: 0.856 +- 0.014
              recall: 0.783 +- 0.107
                  f1: 0.813 +- 0.058
   average_precision: 0.858 +- 0.042
             roc_auc: 0.861 +- 0.009
elapsed: 10.7 sec
Time elapsed: 46.8 sec
Positive
graph grammar stats:
#instances:168   #interfaces: 71   #cores: 40   #core-interface-pairs: 213
Negative
graph grammar stats:
#instances:168   #interfaces: 97   #cores: 47   #core-interface-pairs: 310
================================================================================
repetition: 5/10
training percentage:0.6
--------------------------------------------------------------------------------
working on original
training set sizes: #pos: 168 #neg: 168
Test set
Instances: 240 ; Features: 1048577 with an avg of 298 features per instance
--------------------------------------------------------------------------------
Test Estimate
             precision    recall  f1-score   support

         -1       0.79      0.82      0.80       120
          1       0.82      0.78      0.79       120

avg / total       0.80      0.80      0.80       240

APR: 0.866
ROC: 0.859
Cross-validated estimate
            accuracy: 0.821 +- 0.045
           precision: 0.861 +- 0.031
              recall: 0.767 +- 0.101
                  f1: 0.807 +- 0.061
   average_precision: 0.866 +- 0.049
             roc_auc: 0.876 +- 0.013
elapsed: 6.2 sec
--------------------------------------------------------------------------------
working on sample
training set sizes: #pos: 328 #neg: 320
Test set
Instances: 240 ; Features: 1048577 with an avg of 298 features per instance
--------------------------------------------------------------------------------
Test Estimate
             precision    recall  f1-score   support

         -1       0.80      0.74      0.77       120
          1       0.76      0.82      0.79       120

avg / total       0.78      0.78      0.78       240

APR: 0.833
ROC: 0.830
Cross-validated estimate
            accuracy: 0.804 +- 0.039
           precision: 0.838 +- 0.039
              recall: 0.758 +- 0.093
                  f1: 0.792 +- 0.054
   average_precision: 0.860 +- 0.028
             roc_auc: 0.868 +- 0.005
elapsed: 8.5 sec
--------------------------------------------------------------------------------
working on original+sample
training set sizes: #pos: 496 #neg: 488
Test set
Instances: 240 ; Features: 1048577 with an avg of 298 features per instance
--------------------------------------------------------------------------------
Test Estimate
             precision    recall  f1-score   support

         -1       0.80      0.83      0.82       120
          1       0.83      0.79      0.81       120

avg / total       0.81      0.81      0.81       240

APR: 0.851
ROC: 0.856
Cross-validated estimate
            accuracy: 0.812 +- 0.037
           precision: 0.846 +- 0.021
              recall: 0.767 +- 0.101
                  f1: 0.800 +- 0.055
   average_precision: 0.876 +- 0.009
             roc_auc: 0.870 +- 0.017
elapsed: 11.2 sec
Time elapsed: 48.1 sec
Positive
graph grammar stats:
#instances:168   #interfaces: 71   #cores: 40   #core-interface-pairs: 213
Negative
graph grammar stats:
#instances:168   #interfaces: 97   #cores: 47   #core-interface-pairs: 310
================================================================================
repetition: 6/10
training percentage:0.6
--------------------------------------------------------------------------------
working on original
training set sizes: #pos: 168 #neg: 168
Test set
Instances: 240 ; Features: 1048577 with an avg of 298 features per instance
--------------------------------------------------------------------------------
Test Estimate
             precision    recall  f1-score   support

         -1       0.79      0.82      0.81       120
          1       0.82      0.78      0.80       120

avg / total       0.80      0.80      0.80       240

APR: 0.847
ROC: 0.846
Cross-validated estimate
            accuracy: 0.800 +- 0.050
           precision: 0.828 +- 0.038
              recall: 0.758 +- 0.103
                  f1: 0.788 +- 0.065
   average_precision: 0.864 +- 0.011
             roc_auc: 0.859 +- 0.017
elapsed: 6.0 sec
--------------------------------------------------------------------------------
working on sample
training set sizes: #pos: 328 #neg: 320
Test set
Instances: 240 ; Features: 1048577 with an avg of 298 features per instance
--------------------------------------------------------------------------------
Test Estimate
             precision    recall  f1-score   support

         -1       0.79      0.74      0.76       120
          1       0.76      0.80      0.78       120

avg / total       0.77      0.77      0.77       240

APR: 0.829
ROC: 0.840
Cross-validated estimate
            accuracy: 0.796 +- 0.033
           precision: 0.841 +- 0.035
              recall: 0.733 +- 0.077
                  f1: 0.780 +- 0.047
   average_precision: 0.852 +- 0.026
             roc_auc: 0.857 +- 0.008
elapsed: 8.3 sec
--------------------------------------------------------------------------------
working on original+sample
training set sizes: #pos: 496 #neg: 488
Test set
Instances: 240 ; Features: 1048577 with an avg of 298 features per instance
--------------------------------------------------------------------------------
Test Estimate
             precision    recall  f1-score   support

         -1       0.79      0.80      0.79       120
          1       0.80      0.78      0.79       120

avg / total       0.79      0.79      0.79       240

APR: 0.834
ROC: 0.857
Cross-validated estimate
            accuracy: 0.787 +- 0.044
           precision: 0.826 +- 0.028
              recall: 0.733 +- 0.125
                  f1: 0.769 +- 0.073
   average_precision: 0.855 +- 0.024
             roc_auc: 0.854 +- 0.005
elapsed: 10.4 sec
Time elapsed: 46.0 sec
Positive
graph grammar stats:
#instances:168   #interfaces: 71   #cores: 40   #core-interface-pairs: 213
Negative
graph grammar stats:
#instances:168   #interfaces: 97   #cores: 47   #core-interface-pairs: 310
================================================================================
repetition: 7/10
training percentage:0.6
--------------------------------------------------------------------------------
working on original
training set sizes: #pos: 168 #neg: 168
Test set
Instances: 240 ; Features: 1048577 with an avg of 298 features per instance
--------------------------------------------------------------------------------
Test Estimate
             precision    recall  f1-score   support

         -1       0.81      0.84      0.82       120
          1       0.83      0.80      0.82       120

avg / total       0.82      0.82      0.82       240

APR: 0.853
ROC: 0.849
Cross-validated estimate
            accuracy: 0.796 +- 0.028
           precision: 0.835 +- 0.029
              recall: 0.742 +- 0.085
                  f1: 0.782 +- 0.044
   average_precision: 0.859 +- 0.020
             roc_auc: 0.861 +- 0.006
elapsed: 6.7 sec
--------------------------------------------------------------------------------
working on sample
training set sizes: #pos: 328 #neg: 320
Test set
Instances: 240 ; Features: 1048577 with an avg of 298 features per instance
--------------------------------------------------------------------------------
Test Estimate
             precision    recall  f1-score   support

         -1       0.78      0.72      0.75       120
          1       0.74      0.79      0.77       120

avg / total       0.76      0.76      0.76       240

APR: 0.856
ROC: 0.849
Cross-validated estimate
            accuracy: 0.796 +- 0.024
           precision: 0.832 +- 0.050
              recall: 0.750 +- 0.070
                  f1: 0.785 +- 0.031
   average_precision: 0.860 +- 0.025
             roc_auc: 0.866 +- 0.007
elapsed: 8.5 sec
--------------------------------------------------------------------------------
working on original+sample
training set sizes: #pos: 496 #neg: 488
Test set
Instances: 240 ; Features: 1048577 with an avg of 298 features per instance
--------------------------------------------------------------------------------
Test Estimate
             precision    recall  f1-score   support

         -1       0.80      0.82      0.81       120
          1       0.81      0.80      0.81       120

avg / total       0.81      0.81      0.81       240

APR: 0.860
ROC: 0.863
Cross-validated estimate
            accuracy: 0.817 +- 0.028
           precision: 0.865 +- 0.044
              recall: 0.758 +- 0.096
                  f1: 0.802 +- 0.046
   average_precision: 0.867 +- 0.021
             roc_auc: 0.862 +- 0.011
elapsed: 10.8 sec
Time elapsed: 48.6 sec
Positive
graph grammar stats:
#instances:168   #interfaces: 71   #cores: 40   #core-interface-pairs: 213
Negative
graph grammar stats:
#instances:168   #interfaces: 97   #cores: 47   #core-interface-pairs: 310
================================================================================
repetition: 8/10
training percentage:0.6
--------------------------------------------------------------------------------
working on original
training set sizes: #pos: 168 #neg: 168
Test set
Instances: 240 ; Features: 1048577 with an avg of 298 features per instance
--------------------------------------------------------------------------------
Test Estimate
             precision    recall  f1-score   support

         -1       0.77      0.82      0.79       120
          1       0.80      0.75      0.78       120

avg / total       0.78      0.78      0.78       240

APR: 0.845
ROC: 0.846
Cross-validated estimate
            accuracy: 0.808 +- 0.028
           precision: 0.851 +- 0.057
              recall: 0.758 +- 0.089
                  f1: 0.796 +- 0.042
   average_precision: 0.866 +- 0.032
             roc_auc: 0.867 +- 0.024
elapsed: 6.1 sec
--------------------------------------------------------------------------------
working on sample
training set sizes: #pos: 328 #neg: 320
Test set
Instances: 240 ; Features: 1048577 with an avg of 298 features per instance
--------------------------------------------------------------------------------
Test Estimate
             precision    recall  f1-score   support

         -1       0.82      0.62      0.70       120
          1       0.69      0.87      0.77       120

avg / total       0.76      0.74      0.74       240

APR: 0.816
ROC: 0.830
Cross-validated estimate
            accuracy: 0.800 +- 0.034
           precision: 0.836 +- 0.028
              recall: 0.750 +- 0.099
                  f1: 0.786 +- 0.052
   average_precision: 0.855 +- 0.028
             roc_auc: 0.860 +- 0.010
elapsed: 9.0 sec
--------------------------------------------------------------------------------
working on original+sample
training set sizes: #pos: 496 #neg: 488
Test set
Instances: 240 ; Features: 1048577 with an avg of 298 features per instance
--------------------------------------------------------------------------------
Test Estimate
             precision    recall  f1-score   support

         -1       0.81      0.77      0.79       120
          1       0.78      0.82      0.80       120

avg / total       0.79      0.79      0.79       240

APR: 0.834
ROC: 0.845
Cross-validated estimate
            accuracy: 0.808 +- 0.024
           precision: 0.841 +- 0.068
              recall: 0.775 +- 0.086
                  f1: 0.800 +- 0.033
   average_precision: 0.859 +- 0.040
             roc_auc: 0.868 +- 0.013
elapsed: 10.4 sec
Time elapsed: 46.2 sec
Positive
graph grammar stats:
#instances:168   #interfaces: 71   #cores: 40   #core-interface-pairs: 213
Negative
graph grammar stats:
#instances:168   #interfaces: 97   #cores: 47   #core-interface-pairs: 310
================================================================================
repetition: 9/10
training percentage:0.6
--------------------------------------------------------------------------------
working on original
training set sizes: #pos: 168 #neg: 168
Test set
Instances: 240 ; Features: 1048577 with an avg of 298 features per instance
--------------------------------------------------------------------------------
Test Estimate
             precision    recall  f1-score   support

         -1       0.79      0.82      0.80       120
          1       0.81      0.78      0.80       120

avg / total       0.80      0.80      0.80       240

APR: 0.853
ROC: 0.859
Cross-validated estimate
            accuracy: 0.812 +- 0.029
           precision: 0.844 +- 0.020
              recall: 0.767 +- 0.057
                  f1: 0.802 +- 0.037
   average_precision: 0.855 +- 0.040
             roc_auc: 0.868 +- 0.006
elapsed: 6.3 sec
--------------------------------------------------------------------------------
working on sample
training set sizes: #pos: 328 #neg: 320
Test set
Instances: 240 ; Features: 1048577 with an avg of 298 features per instance
--------------------------------------------------------------------------------
Test Estimate
             precision    recall  f1-score   support

         -1       0.79      0.68      0.73       120
          1       0.72      0.82      0.77       120

avg / total       0.75      0.75      0.75       240

APR: 0.782
ROC: 0.821
Cross-validated estimate
            accuracy: 0.800 +- 0.039
           precision: 0.845 +- 0.050
              recall: 0.742 +- 0.085
                  f1: 0.785 +- 0.051
   average_precision: 0.852 +- 0.049
             roc_auc: 0.857 +- 0.012
elapsed: 9.0 sec
--------------------------------------------------------------------------------
working on original+sample
training set sizes: #pos: 496 #neg: 488
Test set
Instances: 240 ; Features: 1048577 with an avg of 298 features per instance
--------------------------------------------------------------------------------
Test Estimate
             precision    recall  f1-score   support

         -1       0.80      0.82      0.81       120
          1       0.82      0.80      0.81       120

avg / total       0.81      0.81      0.81       240

APR: 0.835
ROC: 0.859
Cross-validated estimate
            accuracy: 0.800 +- 0.047
           precision: 0.825 +- 0.028
              recall: 0.758 +- 0.089
                  f1: 0.789 +- 0.062
   average_precision: 0.848 +- 0.012
             roc_auc: 0.854 +- 0.018
elapsed: 10.7 sec
Time elapsed: 47.6 sec
Positive
graph grammar stats:
#instances:168   #interfaces: 71   #cores: 40   #core-interface-pairs: 213
Negative
graph grammar stats:
#instances:168   #interfaces: 97   #cores: 47   #core-interface-pairs: 310
================================================================================
repetition: 10/10
training percentage:0.6
--------------------------------------------------------------------------------
working on original
training set sizes: #pos: 168 #neg: 168
Test set
Instances: 240 ; Features: 1048577 with an avg of 298 features per instance
--------------------------------------------------------------------------------
Test Estimate
             precision    recall  f1-score   support

         -1       0.77      0.83      0.80       120
          1       0.82      0.75      0.78       120

avg / total       0.79      0.79      0.79       240

APR: 0.840
ROC: 0.842
Cross-validated estimate
            accuracy: 0.804 +- 0.043
           precision: 0.829 +- 0.040
              recall: 0.767 +- 0.082
                  f1: 0.795 +- 0.053
   average_precision: 0.856 +- 0.018
             roc_auc: 0.855 +- 0.021
elapsed: 6.2 sec
--------------------------------------------------------------------------------
working on sample
training set sizes: #pos: 328 #neg: 320
Test set
Instances: 240 ; Features: 1048577 with an avg of 298 features per instance
--------------------------------------------------------------------------------
Test Estimate
             precision    recall  f1-score   support

         -1       0.82      0.65      0.73       120
          1       0.71      0.86      0.78       120

avg / total       0.77      0.75      0.75       240

APR: 0.856
ROC: 0.849
Cross-validated estimate
            accuracy: 0.804 +- 0.041
           precision: 0.838 +- 0.027
              recall: 0.758 +- 0.110
                  f1: 0.790 +- 0.064
   average_precision: 0.870 +- 0.028
             roc_auc: 0.872 +- 0.006
elapsed: 8.1 sec
--------------------------------------------------------------------------------
working on original+sample
training set sizes: #pos: 496 #neg: 488
Test set
Instances: 240 ; Features: 1048577 with an avg of 298 features per instance
--------------------------------------------------------------------------------
Test Estimate
             precision    recall  f1-score   support

         -1       0.82      0.78      0.80       120
          1       0.79      0.82      0.81       120

avg / total       0.80      0.80      0.80       240

APR: 0.859
ROC: 0.869
Cross-validated estimate
            accuracy: 0.800 +- 0.043
           precision: 0.849 +- 0.045
              recall: 0.733 +- 0.086
                  f1: 0.783 +- 0.055
   average_precision: 0.862 +- 0.034
             roc_auc: 0.861 +- 0.004
elapsed: 9.9 sec
Time elapsed: 44.5 sec
Positive
graph grammar stats:
#instances:224   #interfaces: 95   #cores: 52   #core-interface-pairs: 292
Negative
graph grammar stats:
#instances:224   #interfaces: 129   #cores: 51   #core-interface-pairs: 408
================================================================================
repetition: 1/10
training percentage:0.8
--------------------------------------------------------------------------------
working on original
training set sizes: #pos: 224 #neg: 224
Test set
Instances: 240 ; Features: 1048577 with an avg of 298 features per instance
--------------------------------------------------------------------------------
Test Estimate
             precision    recall  f1-score   support

         -1       0.80      0.83      0.82       120
          1       0.83      0.79      0.81       120

avg / total       0.81      0.81      0.81       240

APR: 0.863
ROC: 0.866
Cross-validated estimate
            accuracy: 0.783 +- 0.017
           precision: 0.806 +- 0.023
              recall: 0.750 +- 0.070
                  f1: 0.774 +- 0.031
   average_precision: 0.854 +- 0.026
             roc_auc: 0.863 +- 0.012
elapsed: 6.8 sec
--------------------------------------------------------------------------------
working on sample
training set sizes: #pos: 438 #neg: 432
Test set
Instances: 240 ; Features: 1048577 with an avg of 298 features per instance
--------------------------------------------------------------------------------
Test Estimate
             precision    recall  f1-score   support

         -1       0.84      0.63      0.72       120
          1       0.70      0.88      0.78       120

avg / total       0.77      0.75      0.75       240

APR: 0.841
ROC: 0.844
Cross-validated estimate
            accuracy: 0.808 +- 0.040
           precision: 0.845 +- 0.062
              recall: 0.767 +- 0.111
                  f1: 0.796 +- 0.056
   average_precision: 0.860 +- 0.030
             roc_auc: 0.856 +- 0.015
elapsed: 2592.8 sec
--------------------------------------------------------------------------------
working on original+sample
training set sizes: #pos: 662 #neg: 656
Test set
Instances: 240 ; Features: 1048577 with an avg of 298 features per instance
--------------------------------------------------------------------------------
Test Estimate
             precision    recall  f1-score   support

         -1       0.83      0.80      0.81       120
          1       0.81      0.83      0.82       120

avg / total       0.82      0.82      0.82       240

APR: 0.862
ROC: 0.865
Cross-validated estimate
            accuracy: 0.792 +- 0.044
           precision: 0.835 +- 0.054
              recall: 0.733 +- 0.086
                  f1: 0.777 +- 0.054
   average_precision: 0.850 +- 0.044
             roc_auc: 0.860 +- 0.008
elapsed: 13.9 sec
Time elapsed: 2641.4 sec
Positive
graph grammar stats:
#instances:224   #interfaces: 95   #cores: 52   #core-interface-pairs: 292
Negative
graph grammar stats:
#instances:224   #interfaces: 129   #cores: 51   #core-interface-pairs: 408
================================================================================
repetition: 2/10
training percentage:0.8
--------------------------------------------------------------------------------
working on original
training set sizes: #pos: 224 #neg: 224
Test set
Instances: 240 ; Features: 1048577 with an avg of 298 features per instance
--------------------------------------------------------------------------------
Test Estimate
             precision    recall  f1-score   support

         -1       0.80      0.86      0.83       120
          1       0.85      0.78      0.81       120

avg / total       0.82      0.82      0.82       240

APR: 0.861
ROC: 0.855
Cross-validated estimate
            accuracy: 0.787 +- 0.053
           precision: 0.826 +- 0.052
              recall: 0.733 +- 0.125
                  f1: 0.770 +- 0.079
   average_precision: 0.854 +- 0.023
             roc_auc: 0.864 +- 0.012
elapsed: 7.0 sec
--------------------------------------------------------------------------------
working on sample
training set sizes: #pos: 438 #neg: 432
Test set
Instances: 240 ; Features: 1048577 with an avg of 298 features per instance
--------------------------------------------------------------------------------
Test Estimate
             precision    recall  f1-score   support

         -1       0.86      0.64      0.73       120
          1       0.71      0.89      0.79       120

avg / total       0.78      0.77      0.76       240

APR: 0.814
ROC: 0.843
Cross-validated estimate
            accuracy: 0.796 +- 0.031
           precision: 0.825 +- 0.039
              recall: 0.758 +- 0.100
                  f1: 0.785 +- 0.046
   average_precision: 0.863 +- 0.015
             roc_auc: 0.864 +- 0.011
elapsed: 9.9 sec
--------------------------------------------------------------------------------
working on original+sample
training set sizes: #pos: 662 #neg: 656
Test set
Instances: 240 ; Features: 1048577 with an avg of 298 features per instance
--------------------------------------------------------------------------------
Test Estimate
             precision    recall  f1-score   support

         -1       0.83      0.77      0.80       120
          1       0.78      0.84      0.81       120

avg / total       0.81      0.80      0.80       240

APR: 0.831
ROC: 0.864
Cross-validated estimate
            accuracy: 0.812 +- 0.044
           precision: 0.845 +- 0.057
              recall: 0.775 +- 0.097
                  f1: 0.803 +- 0.056
   average_precision: 0.839 +- 0.054
             roc_auc: 0.849 +- 0.014
elapsed: 12.0 sec
Time elapsed: 56.3 sec
Positive
graph grammar stats:
#instances:224   #interfaces: 95   #cores: 52   #core-interface-pairs: 292
Negative
graph grammar stats:
#instances:224   #interfaces: 129   #cores: 51   #core-interface-pairs: 408
================================================================================
repetition: 3/10
training percentage:0.8
--------------------------------------------------------------------------------
working on original
training set sizes: #pos: 224 #neg: 224
Test set
Instances: 240 ; Features: 1048577 with an avg of 298 features per instance
--------------------------------------------------------------------------------
Test Estimate
             precision    recall  f1-score   support

         -1       0.79      0.83      0.81       120
          1       0.82      0.78      0.80       120

avg / total       0.81      0.80      0.80       240

APR: 0.858
ROC: 0.856
Cross-validated estimate
            accuracy: 0.817 +- 0.024
           precision: 0.849 +- 0.026
              recall: 0.775 +- 0.086
                  f1: 0.806 +- 0.040
   average_precision: 0.849 +- 0.036
             roc_auc: 0.859 +- 0.012
elapsed: 6.9 sec
--------------------------------------------------------------------------------
working on sample
training set sizes: #pos: 438 #neg: 432
Test set
Instances: 240 ; Features: 1048577 with an avg of 298 features per instance
--------------------------------------------------------------------------------
Test Estimate
             precision    recall  f1-score   support

         -1       0.81      0.64      0.72       120
          1       0.70      0.85      0.77       120

avg / total       0.76      0.75      0.74       240

APR: 0.820
ROC: 0.836
Cross-validated estimate
            accuracy: 0.800 +- 0.036
           precision: 0.833 +- 0.056
              recall: 0.758 +- 0.072
                  f1: 0.790 +- 0.042
   average_precision: 0.855 +- 0.023
             roc_auc: 0.856 +- 0.010
elapsed: 10.1 sec
--------------------------------------------------------------------------------
working on original+sample
training set sizes: #pos: 662 #neg: 656
Test set
Instances: 240 ; Features: 1048577 with an avg of 298 features per instance
--------------------------------------------------------------------------------
Test Estimate
             precision    recall  f1-score   support

         -1       0.80      0.77      0.78       120
          1       0.78      0.81      0.79       120

avg / total       0.79      0.79      0.79       240

APR: 0.840
ROC: 0.848
Cross-validated estimate
            accuracy: 0.783 +- 0.049
           precision: 0.813 +- 0.043
              recall: 0.742 +- 0.119
                  f1: 0.769 +- 0.069
   average_precision: 0.858 +- 0.023
             roc_auc: 0.861 +- 0.014
elapsed: 11.9 sec
Time elapsed: 56.1 sec
Positive
graph grammar stats:
#instances:224   #interfaces: 95   #cores: 52   #core-interface-pairs: 292
Negative
graph grammar stats:
#instances:224   #interfaces: 129   #cores: 51   #core-interface-pairs: 408
================================================================================
repetition: 4/10
training percentage:0.8
--------------------------------------------------------------------------------
working on original
training set sizes: #pos: 224 #neg: 224
Test set
Instances: 240 ; Features: 1048577 with an avg of 298 features per instance
--------------------------------------------------------------------------------
Test Estimate
             precision    recall  f1-score   support

         -1       0.79      0.83      0.81       120
          1       0.82      0.78      0.80       120

avg / total       0.81      0.80      0.80       240

APR: 0.847
ROC: 0.851
Cross-validated estimate
            accuracy: 0.812 +- 0.044
           precision: 0.852 +- 0.016
              recall: 0.758 +- 0.113
                  f1: 0.797 +- 0.067
   average_precision: 0.870 +- 0.027
             roc_auc: 0.866 +- 0.011
elapsed: 6.6 sec
--------------------------------------------------------------------------------
working on sample
training set sizes: #pos: 438 #neg: 432
Test set
Instances: 240 ; Features: 1048577 with an avg of 298 features per instance
--------------------------------------------------------------------------------
Test Estimate
             precision    recall  f1-score   support

         -1       0.78      0.71      0.74       120
          1       0.73      0.80      0.76       120

avg / total       0.76      0.75      0.75       240

APR: 0.815
ROC: 0.830
Cross-validated estimate
            accuracy: 0.796 +- 0.042
           precision: 0.815 +- 0.045
              recall: 0.767 +- 0.077
                  f1: 0.788 +- 0.052
   average_precision: 0.858 +- 0.024
             roc_auc: 0.857 +- 0.006
elapsed: 10.0 sec
--------------------------------------------------------------------------------
working on original+sample
training set sizes: #pos: 662 #neg: 656
Test set
Instances: 240 ; Features: 1048577 with an avg of 298 features per instance
--------------------------------------------------------------------------------
Test Estimate
             precision    recall  f1-score   support

         -1       0.82      0.82      0.82       120
          1       0.82      0.82      0.82       120

avg / total       0.82      0.82      0.82       240

APR: 0.848
ROC: 0.865
Cross-validated estimate
            accuracy: 0.792 +- 0.026
           precision: 0.830 +- 0.076
              recall: 0.750 +- 0.065
                  f1: 0.782 +- 0.025
   average_precision: 0.861 +- 0.022
             roc_auc: 0.858 +- 0.012
elapsed: 11.8 sec
Time elapsed: 54.9 sec
Positive
graph grammar stats:
#instances:224   #interfaces: 95   #cores: 52   #core-interface-pairs: 292
Negative
graph grammar stats:
#instances:224   #interfaces: 129   #cores: 51   #core-interface-pairs: 408
================================================================================
repetition: 5/10
training percentage:0.8
--------------------------------------------------------------------------------
working on original
training set sizes: #pos: 224 #neg: 224
Test set
Instances: 240 ; Features: 1048577 with an avg of 298 features per instance
--------------------------------------------------------------------------------
Test Estimate
             precision    recall  f1-score   support

         -1       0.79      0.82      0.80       120
          1       0.81      0.78      0.80       120

avg / total       0.80      0.80      0.80       240

APR: 0.855
ROC: 0.860
Cross-validated estimate
            accuracy: 0.796 +- 0.046
           precision: 0.832 +- 0.050
              recall: 0.742 +- 0.061
                  f1: 0.783 +- 0.053
   average_precision: 0.864 +- 0.028
             roc_auc: 0.868 +- 0.014
elapsed: 6.7 sec
--------------------------------------------------------------------------------
working on sample
training set sizes: #pos: 438 #neg: 432
Test set
Instances: 240 ; Features: 1048577 with an avg of 298 features per instance
--------------------------------------------------------------------------------
Test Estimate
             precision    recall  f1-score   support

         -1       0.81      0.65      0.72       120
          1       0.71      0.85      0.77       120

avg / total       0.76      0.75      0.75       240

APR: 0.835
ROC: 0.836
Cross-validated estimate
            accuracy: 0.800 +- 0.039
           precision: 0.836 +- 0.033
              recall: 0.750 +- 0.095
                  f1: 0.786 +- 0.054
   average_precision: 0.869 +- 0.018
             roc_auc: 0.865 +- 0.009
elapsed: 10.1 sec
--------------------------------------------------------------------------------
working on original+sample
training set sizes: #pos: 662 #neg: 656
Test set
Instances: 240 ; Features: 1048577 with an avg of 298 features per instance
--------------------------------------------------------------------------------
Test Estimate
             precision    recall  f1-score   support

         -1       0.82      0.78      0.80       120
          1       0.79      0.83      0.81       120

avg / total       0.81      0.80      0.80       240

APR: 0.857
ROC: 0.864
Cross-validated estimate
            accuracy: 0.812 +- 0.042
           precision: 0.841 +- 0.035
              recall: 0.775 +- 0.107
                  f1: 0.801 +- 0.059
   average_precision: 0.860 +- 0.025
             roc_auc: 0.861 +- 0.008
elapsed: 12.0 sec
Time elapsed: 54.9 sec
Positive
graph grammar stats:
#instances:224   #interfaces: 95   #cores: 52   #core-interface-pairs: 292
Negative
graph grammar stats:
#instances:224   #interfaces: 129   #cores: 51   #core-interface-pairs: 408
================================================================================
repetition: 6/10
training percentage:0.8
--------------------------------------------------------------------------------
working on original
training set sizes: #pos: 224 #neg: 224
Test set
Instances: 240 ; Features: 1048577 with an avg of 298 features per instance
--------------------------------------------------------------------------------
Test Estimate
             precision    recall  f1-score   support

         -1       0.81      0.82      0.82       120
          1       0.82      0.81      0.82       120

avg / total       0.82      0.82      0.82       240

APR: 0.860
ROC: 0.857
Cross-validated estimate
            accuracy: 0.808 +- 0.044
           precision: 0.836 +- 0.016
              recall: 0.767 +- 0.101
                  f1: 0.796 +- 0.062
   average_precision: 0.863 +- 0.033
             roc_auc: 0.869 +- 0.017
elapsed: 6.4 sec
--------------------------------------------------------------------------------
working on sample
training set sizes: #pos: 438 #neg: 432
Test set
Instances: 240 ; Features: 1048577 with an avg of 298 features per instance
--------------------------------------------------------------------------------
Test Estimate
             precision    recall  f1-score   support

         -1       0.80      0.72      0.76       120
          1       0.75      0.82      0.78       120

avg / total       0.77      0.77      0.77       240

APR: 0.828
ROC: 0.840
Cross-validated estimate
            accuracy: 0.804 +- 0.031
           precision: 0.843 +- 0.020
              recall: 0.750 +- 0.091
                  f1: 0.790 +- 0.049
   average_precision: 0.851 +- 0.024
             roc_auc: 0.861 +- 0.010
elapsed: 9.9 sec
--------------------------------------------------------------------------------
working on original+sample
training set sizes: #pos: 662 #neg: 656
Test set
Instances: 240 ; Features: 1048577 with an avg of 298 features per instance
--------------------------------------------------------------------------------
Test Estimate
             precision    recall  f1-score   support

         -1       0.82      0.80      0.81       120
          1       0.80      0.82      0.81       120

avg / total       0.81      0.81      0.81       240

APR: 0.865
ROC: 0.872
Cross-validated estimate
            accuracy: 0.821 +- 0.045
           precision: 0.862 +- 0.029
              recall: 0.767 +- 0.107
                  f1: 0.807 +- 0.062
   average_precision: 0.869 +- 0.015
             roc_auc: 0.864 +- 0.017
elapsed: 12.1 sec
Time elapsed: 54.5 sec
Positive
graph grammar stats:
#instances:224   #interfaces: 95   #cores: 52   #core-interface-pairs: 292
Negative
graph grammar stats:
#instances:224   #interfaces: 129   #cores: 51   #core-interface-pairs: 408
================================================================================
repetition: 7/10
training percentage:0.8
--------------------------------------------------------------------------------
working on original
training set sizes: #pos: 224 #neg: 224
Test set
Instances: 240 ; Features: 1048577 with an avg of 298 features per instance
--------------------------------------------------------------------------------
Test Estimate
             precision    recall  f1-score   support

         -1       0.78      0.82      0.80       120
          1       0.81      0.78      0.79       120

avg / total       0.80      0.80      0.80       240

APR: 0.851
ROC: 0.853
Cross-validated estimate
            accuracy: 0.804 +- 0.036
           precision: 0.823 +- 0.012
              recall: 0.775 +- 0.094
                  f1: 0.795 +- 0.051
   average_precision: 0.859 +- 0.029
             roc_auc: 0.866 +- 0.016
elapsed: 6.6 sec
--------------------------------------------------------------------------------
working on sample
training set sizes: #pos: 438 #neg: 432
Test set
Instances: 240 ; Features: 1048577 with an avg of 298 features per instance
--------------------------------------------------------------------------------
Test Estimate
             precision    recall  f1-score   support

         -1       0.78      0.61      0.68       120
          1       0.68      0.82      0.74       120

avg / total       0.73      0.72      0.71       240

APR: 0.822
ROC: 0.815
Cross-validated estimate
            accuracy: 0.787 +- 0.052
           precision: 0.820 +- 0.055
              recall: 0.742 +- 0.100
                  f1: 0.774 +- 0.068
   average_precision: 0.864 +- 0.019
             roc_auc: 0.861 +- 0.006
elapsed: 9.9 sec
--------------------------------------------------------------------------------
working on original+sample
training set sizes: #pos: 662 #neg: 656
Test set
Instances: 240 ; Features: 1048577 with an avg of 298 features per instance
--------------------------------------------------------------------------------
Test Estimate
             precision    recall  f1-score   support

         -1       0.78      0.78      0.78       120
          1       0.78      0.78      0.78       120

avg / total       0.78      0.78      0.78       240

APR: 0.854
ROC: 0.852
Cross-validated estimate
            accuracy: 0.817 +- 0.031
           precision: 0.834 +- 0.049
              recall: 0.800 +- 0.100
                  f1: 0.811 +- 0.044
   average_precision: 0.868 +- 0.020
             roc_auc: 0.866 +- 0.008
elapsed: 11.9 sec
Time elapsed: 54.4 sec
Positive
graph grammar stats:
#instances:224   #interfaces: 95   #cores: 52   #core-interface-pairs: 292
Negative
graph grammar stats:
#instances:224   #interfaces: 129   #cores: 51   #core-interface-pairs: 408
================================================================================
repetition: 8/10
training percentage:0.8
--------------------------------------------------------------------------------
working on original
training set sizes: #pos: 224 #neg: 224
Test set
Instances: 240 ; Features: 1048577 with an avg of 298 features per instance
--------------------------------------------------------------------------------
Test Estimate
             precision    recall  f1-score   support

         -1       0.79      0.85      0.82       120
          1       0.84      0.78      0.81       120

avg / total       0.81      0.81      0.81       240

APR: 0.864
ROC: 0.866
Cross-validated estimate
            accuracy: 0.796 +- 0.036
           precision: 0.816 +- 0.023
              recall: 0.767 +- 0.094
                  f1: 0.787 +- 0.053
   average_precision: 0.858 +- 0.011
             roc_auc: 0.856 +- 0.014
elapsed: 6.7 sec
--------------------------------------------------------------------------------
working on sample
training set sizes: #pos: 438 #neg: 432
Test set
Instances: 240 ; Features: 1048577 with an avg of 298 features per instance
--------------------------------------------------------------------------------
Test Estimate
             precision    recall  f1-score   support

         -1       0.82      0.67      0.74       120
          1       0.72      0.86      0.78       120

avg / total       0.77      0.76      0.76       240

APR: 0.831
ROC: 0.837
Cross-validated estimate
            accuracy: 0.804 +- 0.034
           precision: 0.830 +- 0.019
              recall: 0.767 +- 0.086
                  f1: 0.794 +- 0.047
   average_precision: 0.867 +- 0.027
             roc_auc: 0.868 +- 0.012
elapsed: 10.2 sec
--------------------------------------------------------------------------------
working on original+sample
training set sizes: #pos: 662 #neg: 656
Test set
Instances: 240 ; Features: 1048577 with an avg of 298 features per instance
--------------------------------------------------------------------------------
Test Estimate
             precision    recall  f1-score   support

         -1       0.81      0.77      0.79       120
          1       0.78      0.82      0.80       120

avg / total       0.79      0.79      0.79       240

APR: 0.862
ROC: 0.869
Cross-validated estimate
            accuracy: 0.796 +- 0.044
           precision: 0.827 +- 0.040
              recall: 0.750 +- 0.099
                  f1: 0.783 +- 0.060
   average_precision: 0.840 +- 0.041
             roc_auc: 0.848 +- 0.015
elapsed: 12.1 sec
Time elapsed: 54.7 sec
Positive
graph grammar stats:
#instances:224   #interfaces: 95   #cores: 52   #core-interface-pairs: 292
Negative
graph grammar stats:
#instances:224   #interfaces: 129   #cores: 51   #core-interface-pairs: 408
================================================================================
repetition: 9/10
training percentage:0.8
--------------------------------------------------------------------------------
working on original
training set sizes: #pos: 224 #neg: 224
Test set
Instances: 240 ; Features: 1048577 with an avg of 298 features per instance
--------------------------------------------------------------------------------
Test Estimate
             precision    recall  f1-score   support

         -1       0.77      0.82      0.79       120
          1       0.81      0.76      0.78       120

avg / total       0.79      0.79      0.79       240

APR: 0.857
ROC: 0.855
Cross-validated estimate
            accuracy: 0.812 +- 0.044
           precision: 0.845 +- 0.034
              recall: 0.767 +- 0.101
                  f1: 0.800 +- 0.061
   average_precision: 0.863 +- 0.029
             roc_auc: 0.863 +- 0.016
elapsed: 6.4 sec
--------------------------------------------------------------------------------
working on sample
training set sizes: #pos: 438 #neg: 432
Test set
Instances: 240 ; Features: 1048577 with an avg of 298 features per instance
--------------------------------------------------------------------------------
Test Estimate
             precision    recall  f1-score   support

         -1       0.80      0.62      0.70       120
          1       0.69      0.85      0.76       120

avg / total       0.75      0.73      0.73       240

APR: 0.797
ROC: 0.817
Cross-validated estimate
            accuracy: 0.796 +- 0.033
           precision: 0.841 +- 0.033
              recall: 0.733 +- 0.082
                  f1: 0.780 +- 0.048
   average_precision: 0.864 +- 0.027
             roc_auc: 0.866 +- 0.015
elapsed: 10.4 sec
--------------------------------------------------------------------------------
working on original+sample
training set sizes: #pos: 662 #neg: 656
Test set
Instances: 240 ; Features: 1048577 with an avg of 298 features per instance
--------------------------------------------------------------------------------
Test Estimate
             precision    recall  f1-score   support

         -1       0.80      0.74      0.77       120
          1       0.76      0.82      0.79       120

avg / total       0.78      0.78      0.78       240

APR: 0.860
ROC: 0.869
Cross-validated estimate
            accuracy: 0.796 +- 0.040
           precision: 0.826 +- 0.042
              recall: 0.750 +- 0.065
                  f1: 0.785 +- 0.049
   average_precision: 0.855 +- 0.034
             roc_auc: 0.853 +- 0.016
elapsed: 11.9 sec
Time elapsed: 56.4 sec
Positive
graph grammar stats:
#instances:224   #interfaces: 95   #cores: 52   #core-interface-pairs: 292
Negative
graph grammar stats:
#instances:224   #interfaces: 129   #cores: 51   #core-interface-pairs: 408
================================================================================
repetition: 10/10
training percentage:0.8
--------------------------------------------------------------------------------
working on original
training set sizes: #pos: 224 #neg: 224
Test set
Instances: 240 ; Features: 1048577 with an avg of 298 features per instance
--------------------------------------------------------------------------------
Test Estimate
             precision    recall  f1-score   support

         -1       0.80      0.84      0.82       120
          1       0.83      0.78      0.81       120

avg / total       0.81      0.81      0.81       240

APR: 0.865
ROC: 0.869
Cross-validated estimate
            accuracy: 0.792 +- 0.029
           precision: 0.823 +- 0.034
              recall: 0.750 +- 0.095
                  f1: 0.779 +- 0.047
   average_precision: 0.860 +- 0.021
             roc_auc: 0.858 +- 0.012
elapsed: 6.8 sec
--------------------------------------------------------------------------------
working on sample
training set sizes: #pos: 438 #neg: 432
Test set
Instances: 240 ; Features: 1048577 with an avg of 298 features per instance
--------------------------------------------------------------------------------
Test Estimate
             precision    recall  f1-score   support

         -1       0.86      0.61      0.71       120
          1       0.70      0.90      0.79       120

avg / total       0.78      0.75      0.75       240

APR: 0.804
ROC: 0.824
Cross-validated estimate
            accuracy: 0.825 +- 0.031
           precision: 0.851 +- 0.035
              recall: 0.792 +- 0.070
                  f1: 0.818 +- 0.038
   average_precision: 0.862 +- 0.012
             roc_auc: 0.867 +- 0.021
elapsed: 10.3 sec
--------------------------------------------------------------------------------
working on original+sample
training set sizes: #pos: 662 #neg: 656
Test set
Instances: 240 ; Features: 1048577 with an avg of 298 features per instance
--------------------------------------------------------------------------------
Test Estimate
             precision    recall  f1-score   support

         -1       0.83      0.76      0.79       120
          1       0.78      0.84      0.81       120

avg / total       0.80      0.80      0.80       240

APR: 0.848
ROC: 0.864
Cross-validated estimate
            accuracy: 0.792 +- 0.026
           precision: 0.826 +- 0.054
              recall: 0.750 +- 0.091
                  f1: 0.780 +- 0.042
   average_precision: 0.843 +- 0.043
             roc_auc: 0.856 +- 0.009
elapsed: 12.2 sec
Time elapsed: 56.7 sec
Positive
graph grammar stats:
#instances:266   #interfaces: 117   #cores: 55   #core-interface-pairs: 357
Negative
graph grammar stats:
#instances:266   #interfaces: 153   #cores: 51   #core-interface-pairs: 474
================================================================================
repetition: 1/10
training percentage:0.95
--------------------------------------------------------------------------------
working on original
training set sizes: #pos: 266 #neg: 266
Test set
Instances: 240 ; Features: 1048577 with an avg of 298 features per instance
--------------------------------------------------------------------------------
Test Estimate
             precision    recall  f1-score   support

         -1       0.83      0.88      0.85       120
          1       0.87      0.82      0.84       120

avg / total       0.85      0.85      0.85       240

APR: 0.878
ROC: 0.876
Cross-validated estimate
            accuracy: 0.792 +- 0.049
           precision: 0.830 +- 0.048
              recall: 0.733 +- 0.077
                  f1: 0.777 +- 0.061
   average_precision: 0.855 +- 0.043
             roc_auc: 0.858 +- 0.015
elapsed: 7.3 sec
--------------------------------------------------------------------------------
working on sample
training set sizes: #pos: 522 #neg: 514
Test set
Instances: 240 ; Features: 1048577 with an avg of 298 features per instance
--------------------------------------------------------------------------------
Test Estimate
             precision    recall  f1-score   support

         -1       0.79      0.69      0.74       120
          1       0.73      0.82      0.77       120

avg / total       0.76      0.75      0.75       240

APR: 0.841
ROC: 0.851
Cross-validated estimate
            accuracy: 0.808 +- 0.046
           precision: 0.847 +- 0.044
              recall: 0.758 +- 0.110
                  f1: 0.794 +- 0.067
   average_precision: 0.868 +- 0.015
             roc_auc: 0.866 +- 0.014
elapsed: 11.1 sec
--------------------------------------------------------------------------------
working on original+sample
training set sizes: #pos: 788 #neg: 780
Test set
Instances: 240 ; Features: 1048577 with an avg of 298 features per instance
--------------------------------------------------------------------------------
Test Estimate
             precision    recall  f1-score   support

         -1       0.82      0.83      0.83       120
          1       0.83      0.82      0.82       120

avg / total       0.83      0.82      0.82       240

APR: 0.880
ROC: 0.886
Cross-validated estimate
            accuracy: 0.812 +- 0.037
           precision: 0.853 +- 0.032
              recall: 0.758 +- 0.093
                  f1: 0.799 +- 0.054
   average_precision: 0.865 +- 0.017
             roc_auc: 0.869 +- 0.016
elapsed: 13.5 sec
Time elapsed: 64.6 sec
Positive
graph grammar stats:
#instances:266   #interfaces: 117   #cores: 55   #core-interface-pairs: 357
Negative
graph grammar stats:
#instances:266   #interfaces: 153   #cores: 51   #core-interface-pairs: 474
================================================================================
repetition: 2/10
training percentage:0.95
--------------------------------------------------------------------------------
working on original
training set sizes: #pos: 266 #neg: 266
Test set
Instances: 240 ; Features: 1048577 with an avg of 298 features per instance
--------------------------------------------------------------------------------
Test Estimate
             precision    recall  f1-score   support

         -1       0.80      0.86      0.83       120
          1       0.85      0.79      0.82       120

avg / total       0.83      0.82      0.82       240

APR: 0.880
ROC: 0.878
Cross-validated estimate
            accuracy: 0.792 +- 0.026
           precision: 0.823 +- 0.044
              recall: 0.750 +- 0.075
                  f1: 0.781 +- 0.036
   average_precision: 0.849 +- 0.023
             roc_auc: 0.857 +- 0.015
elapsed: 7.4 sec
--------------------------------------------------------------------------------
working on sample
training set sizes: #pos: 522 #neg: 514
Test set
Instances: 240 ; Features: 1048577 with an avg of 298 features per instance
--------------------------------------------------------------------------------
Test Estimate
             precision    recall  f1-score   support

         -1       0.79      0.62      0.70       120
          1       0.69      0.83      0.75       120

avg / total       0.74      0.73      0.73       240

APR: 0.806
ROC: 0.827
Cross-validated estimate
            accuracy: 0.804 +- 0.043
           precision: 0.836 +- 0.037
              recall: 0.758 +- 0.089
                  f1: 0.792 +- 0.058
   average_precision: 0.867 +- 0.035
             roc_auc: 0.869 +- 0.018
elapsed: 21.5 sec
--------------------------------------------------------------------------------
working on original+sample
training set sizes: #pos: 788 #neg: 780
Test set
Instances: 240 ; Features: 1048577 with an avg of 298 features per instance
--------------------------------------------------------------------------------
Test Estimate
             precision    recall  f1-score   support

         -1       0.81      0.79      0.80       120
          1       0.80      0.81      0.80       120

avg / total       0.80      0.80      0.80       240

APR: 0.839
ROC: 0.855
Cross-validated estimate
            accuracy: 0.817 +- 0.024
           precision: 0.852 +- 0.041
              recall: 0.775 +- 0.094
                  f1: 0.806 +- 0.039
   average_precision: 0.867 +- 0.012
             roc_auc: 0.863 +- 0.013
elapsed: 38.7 sec
Time elapsed: 100.8 sec
Positive
graph grammar stats:
#instances:266   #interfaces: 117   #cores: 55   #core-interface-pairs: 357
Negative
graph grammar stats:
#instances:266   #interfaces: 153   #cores: 51   #core-interface-pairs: 474
================================================================================
repetition: 3/10
training percentage:0.95
--------------------------------------------------------------------------------
working on original
training set sizes: #pos: 266 #neg: 266
Test set
Instances: 240 ; Features: 1048577 with an avg of 298 features per instance
--------------------------------------------------------------------------------
Test Estimate
             precision    recall  f1-score   support

         -1       0.82      0.83      0.83       120
          1       0.83      0.82      0.82       120

avg / total       0.83      0.82      0.82       240

APR: 0.870
ROC: 0.874
Cross-validated estimate
            accuracy: 0.792 +- 0.054
           precision: 0.816 +- 0.034
              recall: 0.750 +- 0.105
                  f1: 0.779 +- 0.074
   average_precision: 0.842 +- 0.030
             roc_auc: 0.852 +- 0.003
elapsed: 9.0 sec
--------------------------------------------------------------------------------
working on sample
training set sizes: #pos: 522 #neg: 514
Test set
Instances: 240 ; Features: 1048577 with an avg of 298 features per instance
--------------------------------------------------------------------------------
Test Estimate
             precision    recall  f1-score   support

         -1       0.80      0.66      0.72       120
          1       0.71      0.83      0.77       120

avg / total       0.75      0.75      0.74       240

APR: 0.818
ROC: 0.829
Cross-validated estimate
            accuracy: 0.808 +- 0.033
           precision: 0.857 +- 0.058
              recall: 0.750 +- 0.087
                  f1: 0.794 +- 0.046
   average_precision: 0.857 +- 0.051
             roc_auc: 0.865 +- 0.012
elapsed: 20.6 sec
--------------------------------------------------------------------------------
working on original+sample
training set sizes: #pos: 788 #neg: 780
Test set
Instances: 240 ; Features: 1048577 with an avg of 298 features per instance
--------------------------------------------------------------------------------
Test Estimate
             precision    recall  f1-score   support

         -1       0.82      0.77      0.79       120
          1       0.78      0.83      0.81       120

avg / total       0.80      0.80      0.80       240

APR: 0.868
ROC: 0.869
Cross-validated estimate
            accuracy: 0.800 +- 0.025
           precision: 0.842 +- 0.020
              recall: 0.742 +- 0.081
                  f1: 0.785 +- 0.043
   average_precision: 0.855 +- 0.018
             roc_auc: 0.857 +- 0.015
elapsed: 23.8 sec
Time elapsed: 93.3 sec
Positive
graph grammar stats:
#instances:266   #interfaces: 117   #cores: 55   #core-interface-pairs: 357
Negative
graph grammar stats:
#instances:266   #interfaces: 153   #cores: 51   #core-interface-pairs: 474
================================================================================
repetition: 4/10
training percentage:0.95
--------------------------------------------------------------------------------
working on original
training set sizes: #pos: 266 #neg: 266
Test set
Instances: 240 ; Features: 1048577 with an avg of 298 features per instance
--------------------------------------------------------------------------------
Test Estimate
             precision    recall  f1-score   support

         -1       0.83      0.86      0.84       120
          1       0.85      0.82      0.84       120

avg / total       0.84      0.84      0.84       240

APR: 0.874
ROC: 0.875
Cross-validated estimate
            accuracy: 0.808 +- 0.020
           precision: 0.834 +- 0.033
              recall: 0.775 +- 0.077
                  f1: 0.800 +- 0.034
   average_precision: 0.855 +- 0.034
             roc_auc: 0.863 +- 0.008
elapsed: 8.1 sec
--------------------------------------------------------------------------------
working on sample
training set sizes: #pos: 522 #neg: 514
Test set
Instances: 240 ; Features: 1048577 with an avg of 298 features per instance
--------------------------------------------------------------------------------
Test Estimate
             precision    recall  f1-score   support

         -1       0.86      0.67      0.75       120
          1       0.73      0.89      0.80       120

avg / total       0.79      0.78      0.78       240

APR: 0.837
ROC: 0.861
Cross-validated estimate
            accuracy: 0.796 +- 0.042
           precision: 0.841 +- 0.042
              recall: 0.733 +- 0.101
                  f1: 0.779 +- 0.058
   average_precision: 0.856 +- 0.026
             roc_auc: 0.856 +- 0.011
elapsed: 17.3 sec
--------------------------------------------------------------------------------
working on original+sample
training set sizes: #pos: 788 #neg: 780
Test set
Instances: 240 ; Features: 1048577 with an avg of 298 features per instance
--------------------------------------------------------------------------------
Test Estimate
             precision    recall  f1-score   support

         -1       0.81      0.76      0.78       120
          1       0.77      0.82      0.79       120

avg / total       0.79      0.79      0.79       240

APR: 0.853
ROC: 0.869
Cross-validated estimate
            accuracy: 0.817 +- 0.031
           precision: 0.848 +- 0.030
              recall: 0.775 +- 0.086
                  f1: 0.806 +- 0.044
   average_precision: 0.868 +- 0.014
             roc_auc: 0.863 +- 0.015
elapsed: 25.2 sec
Time elapsed: 87.9 sec
Positive
graph grammar stats:
#instances:266   #interfaces: 117   #cores: 55   #core-interface-pairs: 357
Negative
graph grammar stats:
#instances:266   #interfaces: 153   #cores: 51   #core-interface-pairs: 474
================================================================================
repetition: 5/10
training percentage:0.95
--------------------------------------------------------------------------------
working on original
training set sizes: #pos: 266 #neg: 266
Test set
Instances: 240 ; Features: 1048577 with an avg of 298 features per instance
--------------------------------------------------------------------------------
Test Estimate
             precision    recall  f1-score   support

         -1       0.82      0.83      0.83       120
          1       0.83      0.82      0.82       120

avg / total       0.83      0.82      0.82       240

APR: 0.864
ROC: 0.870
Cross-validated estimate
            accuracy: 0.787 +- 0.036
           precision: 0.826 +- 0.042
              recall: 0.733 +- 0.086
                  f1: 0.773 +- 0.050
   average_precision: 0.864 +- 0.011
             roc_auc: 0.860 +- 0.015
elapsed: 13.2 sec

In [16]:
#setup
dataset_names = !cat NCI60/names
random.shuffle(dataset_names)

In [ ]:
%%time
for dataset in dataset_names:
    #logging
    logger = logging.getLogger()
    if True:
        logger_fname = '%s_predictive_performance_of_samples.log'%dataset
    else:
        logger_fname = None
    configure_logging(logger,verbosity=1, filename=logger_fname)
    
    #main 
    start=time()
    print( 'Working with dataset: %s' % dataset )

    logger.info( 'Working with dataset: %s' % dataset )
    pos_dataset_fname = 'NCI60/' + dataset + '_orig_pos.gspan'
    neg_dataset_fname = 'NCI60/' + dataset + '_orig_neg.gspan'
    #pos_dataset_fname = 'bursi.pos.gspan'
    #neg_dataset_fname = 'bursi.neg.gspan'

    percentages=[.05,.2,.4,.6,.8,.95]

    original_repetitions,\
    original_sample_repetitions,\
    sample_repetitions = evaluate(pos_dataset_fname,
                                  neg_dataset_fname,
                                  size=400,
                                  percentages=percentages,
                                  n_repetitions=3,
                                  train_test_split=0.7)
    #save and display results
    result_fname='%s_predictive_performance_of_samples.data'%dataset
    save_results(result_fname,percentages, original_repetitions,original_sample_repetitions,sample_repetitions)    
    percentages_l, original_repetitions_l,original_sample_repetitions_l,sample_repetitions_l = load_results(result_fname)
    plot(dataset, percentages_l, original_sample_repetitions_l, original_repetitions_l, sample_repetitions_l)
    
    print('Time elapsed: %s'%(datetime.timedelta(seconds=(time() - start))))

In [ ]:
#display
for dataset in dataset_names:
    result_fname='%s_predictive_performance_of_samples.data'%dataset
    percentages_l, original_repetitions_l,original_sample_repetitions_l,sample_repetitions_l = load_results(result_fname)
    plot(dataset, percentages_l, original_sample_repetitions_l, original_repetitions_l, sample_repetitions_l)

.