In [1]:

    

import MLModelCreatorWord as md

doc_table = "author_study_six"


    

In [2]:

    

(features, labels, groups, samples) = md.loadData(doc_table)


    

    




Execution completed
Read completed
Number of rows: 10400
<type 'list'>
doc_id         int64
author_id      int64
feature1     float64
feature2     float64
feature3     float64
feature4     float64
feature5     float64
feature6     float64
feature7     float64
feature8     float64
dtype: object
Data Frame created: Shape: (10400, 10)
Author:   124  Size:  1600
Author:   114  Size:  2400
Author:  1228  Size:  1600
Author:  1472  Size:  3200
Author:  1492  Size:  1600
Min: 1600
Max: 3200
Authors [124, 114, 1228, 1472, 1492].
Found 10400 texts.
Found 10400 features.
Found 10400 groups.

In [3]:

    

logo = md.preProcessTrainVal(features, labels, groups)


    

    




13

In [4]:

    

model = md.compileModel()


    

In [5]:

    

for train_index, test_index in logo.split(features, labels, groups):
        
    model = md.compileModel()

    trainX = features[train_index]
    valX = features[test_index]

    trainY, valY = labels[train_index], labels[test_index]

    (model, train_acc, val_acc) = md.fitModel(model, trainX, trainY, valX, valY)

    del model


    

    





Final Train Accuracy: 100.00

Final Validation Accuracy: 0.00


Final Train Accuracy: 100.00

Final Validation Accuracy: 0.00


Final Train Accuracy: 100.00

Final Validation Accuracy: 0.00


Final Train Accuracy: 100.00

Final Validation Accuracy: 0.00


Final Train Accuracy: 100.00

Final Validation Accuracy: 0.00


Final Train Accuracy: 100.00

Final Validation Accuracy: 0.00


Final Train Accuracy: 100.00

Final Validation Accuracy: 73.38


Final Train Accuracy: 100.00

Final Validation Accuracy: 25.00


Final Train Accuracy: 100.00

Final Validation Accuracy: 25.00


Final Train Accuracy: 100.00

Final Validation Accuracy: 12.62


Final Train Accuracy: 100.00

Final Validation Accuracy: 25.00


Final Train Accuracy: 100.00

Final Validation Accuracy: 5.50


Final Train Accuracy: 100.00

Final Validation Accuracy: 25.00

In [6]:

    

%tb


    

    




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