In [31]:
import pandas as pd
benchmark_data = pd.read_csv('sklearn-benchmark-data.tsv.gz', sep='\t')
benchmark_data.head()
benchmark_data.rename(columns={'heart-c':'Dataset_Name',
'GradientBoostingClassifier':'Method_Name',
'loss=exponential,learning_rate=10.0,n_estimators=100,max_depth=3,max_features=sqrt,warm_start=True':
'Parameters',
'0.723684210526':'Test_Score'},inplace=True)
In [167]:
methodNames_list = benchmark_data['Method_Name'].unique().tolist()
#methodNames_list
In [3]:
methodWiseData = {}
for name in methodNames_list:
methodWiseData[name] = benchmark_data[(benchmark_data.Method_Name == name)]
In [160]:
#for i in names_list:
# print(d[i])
import os
if not os.path.isdir('newBenchmark_results'):
os.mkdir('newBenchmark_results')
gb = methodWiseData['GradientBoostingClassifier']
gb.to_pickle('newBenchmark_results/GradientBoostingClassifier_results.tsv.gz')
In [161]:
method_data = pd.read_pickle('newBenchmark_results/GradientBoostingClassifier-benchmark_results.tsv.gz')
method_data
Out[161]:
Dataset_Name
Method_Name
Parameters
Test_Score
0
heart-c
GradientBoostingClassifier
loss=exponential,learning_rate=10.0,n_estimato...
0.736842
1
heart-c
GradientBoostingClassifier
loss=exponential,learning_rate=10.0,n_estimato...
0.815789
2
heart-c
GradientBoostingClassifier
loss=exponential,learning_rate=10.0,n_estimato...
0.802632
3
heart-c
GradientBoostingClassifier
loss=exponential,learning_rate=10.0,n_estimato...
0.750000
4
heart-c
GradientBoostingClassifier
loss=exponential,learning_rate=10.0,n_estimato...
0.815789
5
heart-c
GradientBoostingClassifier
loss=exponential,learning_rate=10.0,n_estimato...
0.684211
6
heart-c
GradientBoostingClassifier
loss=exponential,learning_rate=10.0,n_estimato...
0.763158
7
heart-c
GradientBoostingClassifier
loss=exponential,learning_rate=10.0,n_estimato...
0.750000
8
heart-c
GradientBoostingClassifier
loss=exponential,learning_rate=10.0,n_estimato...
0.710526
9
heart-c
GradientBoostingClassifier
loss=exponential,learning_rate=10.0,n_estimato...
0.776316
10
heart-c
GradientBoostingClassifier
loss=exponential,learning_rate=10.0,n_estimato...
0.723684
11
heart-c
GradientBoostingClassifier
loss=exponential,learning_rate=10.0,n_estimato...
0.736842
12
heart-c
GradientBoostingClassifier
loss=exponential,learning_rate=10.0,n_estimato...
0.789474
13
heart-c
GradientBoostingClassifier
loss=exponential,learning_rate=10.0,n_estimato...
0.789474
14
heart-c
GradientBoostingClassifier
loss=exponential,learning_rate=10.0,n_estimato...
0.736842
15
heart-c
GradientBoostingClassifier
loss=exponential,learning_rate=10.0,n_estimato...
0.736842
16
heart-c
GradientBoostingClassifier
loss=exponential,learning_rate=10.0,n_estimato...
0.776316
17
heart-c
GradientBoostingClassifier
loss=exponential,learning_rate=10.0,n_estimato...
0.763158
18
heart-c
GradientBoostingClassifier
loss=exponential,learning_rate=10.0,n_estimato...
0.802632
19
heart-c
GradientBoostingClassifier
loss=exponential,learning_rate=10.0,n_estimato...
0.815789
20
heart-c
GradientBoostingClassifier
loss=exponential,learning_rate=10.0,n_estimato...
0.828947
21
heart-c
GradientBoostingClassifier
loss=exponential,learning_rate=10.0,n_estimato...
0.736842
22
heart-c
GradientBoostingClassifier
loss=exponential,learning_rate=10.0,n_estimato...
0.736842
23
heart-c
GradientBoostingClassifier
loss=exponential,learning_rate=10.0,n_estimato...
0.750000
24
heart-c
GradientBoostingClassifier
loss=exponential,learning_rate=10.0,n_estimato...
0.789474
25
heart-c
GradientBoostingClassifier
loss=exponential,learning_rate=10.0,n_estimato...
0.815789
26
heart-c
GradientBoostingClassifier
loss=exponential,learning_rate=10.0,n_estimato...
0.697368
27
heart-c
GradientBoostingClassifier
loss=exponential,learning_rate=10.0,n_estimato...
0.842105
28
heart-c
GradientBoostingClassifier
loss=exponential,learning_rate=10.0,n_estimato...
0.776316
29
shuttle-landing-control
GradientBoostingClassifier
loss=deviance,learning_rate=50.0,n_estimators=...
0.750000
...
...
...
...
...
2162999
shuttle-landing-control
GradientBoostingClassifier
loss=deviance,learning_rate=0.5,n_estimators=1...
0.500000
2163000
shuttle-landing-control
GradientBoostingClassifier
loss=deviance,learning_rate=0.5,n_estimators=1...
0.750000
2163001
shuttle-landing-control
GradientBoostingClassifier
loss=deviance,learning_rate=0.5,n_estimators=1...
0.750000
2163002
shuttle-landing-control
GradientBoostingClassifier
loss=deviance,learning_rate=0.5,n_estimators=1...
0.500000
2163003
shuttle-landing-control
GradientBoostingClassifier
loss=deviance,learning_rate=0.5,n_estimators=1...
0.750000
2163004
shuttle-landing-control
GradientBoostingClassifier
loss=deviance,learning_rate=0.5,n_estimators=1...
0.750000
2163005
shuttle-landing-control
GradientBoostingClassifier
loss=deviance,learning_rate=0.5,n_estimators=1...
0.750000
2163006
shuttle-landing-control
GradientBoostingClassifier
loss=deviance,learning_rate=0.5,n_estimators=1...
0.250000
2163007
shuttle-landing-control
GradientBoostingClassifier
loss=deviance,learning_rate=0.5,n_estimators=1...
0.750000
2163008
shuttle-landing-control
GradientBoostingClassifier
loss=deviance,learning_rate=0.5,n_estimators=1...
0.750000
2163009
shuttle-landing-control
GradientBoostingClassifier
loss=deviance,learning_rate=0.5,n_estimators=1...
1.000000
2163010
shuttle-landing-control
GradientBoostingClassifier
loss=deviance,learning_rate=0.5,n_estimators=1...
0.500000
2163011
shuttle-landing-control
GradientBoostingClassifier
loss=deviance,learning_rate=0.5,n_estimators=1...
1.000000
2163012
shuttle-landing-control
GradientBoostingClassifier
loss=deviance,learning_rate=0.5,n_estimators=1...
0.750000
2163013
shuttle-landing-control
GradientBoostingClassifier
loss=deviance,learning_rate=0.5,n_estimators=1...
0.750000
2163014
shuttle-landing-control
GradientBoostingClassifier
loss=deviance,learning_rate=0.5,n_estimators=1...
0.750000
2163015
shuttle-landing-control
GradientBoostingClassifier
loss=deviance,learning_rate=0.5,n_estimators=1...
0.750000
2163016
shuttle-landing-control
GradientBoostingClassifier
loss=deviance,learning_rate=0.5,n_estimators=1...
0.750000
2163017
shuttle-landing-control
GradientBoostingClassifier
loss=deviance,learning_rate=0.5,n_estimators=1...
0.500000
2163018
shuttle-landing-control
GradientBoostingClassifier
loss=deviance,learning_rate=0.5,n_estimators=1...
0.500000
2163019
shuttle-landing-control
GradientBoostingClassifier
loss=deviance,learning_rate=0.5,n_estimators=1...
0.500000
2163020
shuttle-landing-control
GradientBoostingClassifier
loss=deviance,learning_rate=0.5,n_estimators=1...
0.500000
2163021
shuttle-landing-control
GradientBoostingClassifier
loss=deviance,learning_rate=0.5,n_estimators=1...
0.750000
2163022
shuttle-landing-control
GradientBoostingClassifier
loss=deviance,learning_rate=0.5,n_estimators=1...
0.750000
2163023
shuttle-landing-control
GradientBoostingClassifier
loss=deviance,learning_rate=0.5,n_estimators=1...
1.000000
2163024
shuttle-landing-control
GradientBoostingClassifier
loss=deviance,learning_rate=0.5,n_estimators=1...
0.500000
2163025
shuttle-landing-control
GradientBoostingClassifier
loss=deviance,learning_rate=0.5,n_estimators=1...
0.500000
2163026
shuttle-landing-control
GradientBoostingClassifier
loss=deviance,learning_rate=0.5,n_estimators=1...
0.500000
2163027
shuttle-landing-control
GradientBoostingClassifier
loss=deviance,learning_rate=0.5,n_estimators=1...
0.250000
2163028
shuttle-landing-control
GradientBoostingClassifier
loss=deviance,learning_rate=0.5,n_estimators=1...
0.500000
1527509 rows × 4 columns
In [162]:
method_param = pd.DataFrame(method_data.Parameters.str.split(',').tolist(),
columns = ['Param1','Param2','Param3'])
method_param
Out[162]:
Param1
Param2
Param3
Param4
Param5
Param6
0
loss=exponential
learning_rate=10.0
n_estimators=100
max_depth=3
max_features=sqrt
warm_start=True
1
loss=exponential
learning_rate=10.0
n_estimators=100
max_depth=3
max_features=sqrt
warm_start=True
2
loss=exponential
learning_rate=10.0
n_estimators=100
max_depth=3
max_features=sqrt
warm_start=True
3
loss=exponential
learning_rate=10.0
n_estimators=100
max_depth=3
max_features=sqrt
warm_start=True
4
loss=exponential
learning_rate=10.0
n_estimators=100
max_depth=3
max_features=sqrt
warm_start=True
5
loss=exponential
learning_rate=10.0
n_estimators=100
max_depth=3
max_features=sqrt
warm_start=True
6
loss=exponential
learning_rate=10.0
n_estimators=100
max_depth=3
max_features=sqrt
warm_start=True
7
loss=exponential
learning_rate=10.0
n_estimators=100
max_depth=3
max_features=sqrt
warm_start=True
8
loss=exponential
learning_rate=10.0
n_estimators=100
max_depth=3
max_features=sqrt
warm_start=True
9
loss=exponential
learning_rate=10.0
n_estimators=100
max_depth=3
max_features=sqrt
warm_start=True
10
loss=exponential
learning_rate=10.0
n_estimators=100
max_depth=3
max_features=sqrt
warm_start=True
11
loss=exponential
learning_rate=10.0
n_estimators=100
max_depth=3
max_features=sqrt
warm_start=True
12
loss=exponential
learning_rate=10.0
n_estimators=100
max_depth=3
max_features=sqrt
warm_start=True
13
loss=exponential
learning_rate=10.0
n_estimators=100
max_depth=3
max_features=sqrt
warm_start=True
14
loss=exponential
learning_rate=10.0
n_estimators=100
max_depth=3
max_features=sqrt
warm_start=True
15
loss=exponential
learning_rate=10.0
n_estimators=100
max_depth=3
max_features=sqrt
warm_start=True
16
loss=exponential
learning_rate=10.0
n_estimators=100
max_depth=3
max_features=sqrt
warm_start=True
17
loss=exponential
learning_rate=10.0
n_estimators=100
max_depth=3
max_features=sqrt
warm_start=True
18
loss=exponential
learning_rate=10.0
n_estimators=100
max_depth=3
max_features=sqrt
warm_start=True
19
loss=exponential
learning_rate=10.0
n_estimators=100
max_depth=3
max_features=sqrt
warm_start=True
20
loss=exponential
learning_rate=10.0
n_estimators=100
max_depth=3
max_features=sqrt
warm_start=True
21
loss=exponential
learning_rate=10.0
n_estimators=100
max_depth=3
max_features=sqrt
warm_start=True
22
loss=exponential
learning_rate=10.0
n_estimators=100
max_depth=3
max_features=sqrt
warm_start=True
23
loss=exponential
learning_rate=10.0
n_estimators=100
max_depth=3
max_features=sqrt
warm_start=True
24
loss=exponential
learning_rate=10.0
n_estimators=100
max_depth=3
max_features=sqrt
warm_start=True
25
loss=exponential
learning_rate=10.0
n_estimators=100
max_depth=3
max_features=sqrt
warm_start=True
26
loss=exponential
learning_rate=10.0
n_estimators=100
max_depth=3
max_features=sqrt
warm_start=True
27
loss=exponential
learning_rate=10.0
n_estimators=100
max_depth=3
max_features=sqrt
warm_start=True
28
loss=exponential
learning_rate=10.0
n_estimators=100
max_depth=3
max_features=sqrt
warm_start=True
29
loss=deviance
learning_rate=50.0
n_estimators=10
max_depth=2
max_features=log2
warm_start=True
...
...
...
...
...
...
...
1527479
loss=deviance
learning_rate=0.5
n_estimators=1000
max_depth=2
max_features=0.75
warm_start=True
1527480
loss=deviance
learning_rate=0.5
n_estimators=1000
max_depth=2
max_features=0.75
warm_start=True
1527481
loss=deviance
learning_rate=0.5
n_estimators=1000
max_depth=2
max_features=0.75
warm_start=True
1527482
loss=deviance
learning_rate=0.5
n_estimators=1000
max_depth=2
max_features=0.75
warm_start=True
1527483
loss=deviance
learning_rate=0.5
n_estimators=1000
max_depth=2
max_features=0.75
warm_start=True
1527484
loss=deviance
learning_rate=0.5
n_estimators=1000
max_depth=2
max_features=0.75
warm_start=True
1527485
loss=deviance
learning_rate=0.5
n_estimators=1000
max_depth=2
max_features=0.75
warm_start=True
1527486
loss=deviance
learning_rate=0.5
n_estimators=1000
max_depth=2
max_features=0.75
warm_start=True
1527487
loss=deviance
learning_rate=0.5
n_estimators=1000
max_depth=2
max_features=0.75
warm_start=True
1527488
loss=deviance
learning_rate=0.5
n_estimators=1000
max_depth=2
max_features=0.75
warm_start=True
1527489
loss=deviance
learning_rate=0.5
n_estimators=1000
max_depth=2
max_features=0.75
warm_start=True
1527490
loss=deviance
learning_rate=0.5
n_estimators=1000
max_depth=2
max_features=0.75
warm_start=True
1527491
loss=deviance
learning_rate=0.5
n_estimators=1000
max_depth=2
max_features=0.75
warm_start=True
1527492
loss=deviance
learning_rate=0.5
n_estimators=1000
max_depth=2
max_features=0.75
warm_start=True
1527493
loss=deviance
learning_rate=0.5
n_estimators=1000
max_depth=2
max_features=0.75
warm_start=True
1527494
loss=deviance
learning_rate=0.5
n_estimators=1000
max_depth=2
max_features=0.75
warm_start=True
1527495
loss=deviance
learning_rate=0.5
n_estimators=1000
max_depth=2
max_features=0.75
warm_start=True
1527496
loss=deviance
learning_rate=0.5
n_estimators=1000
max_depth=2
max_features=0.75
warm_start=True
1527497
loss=deviance
learning_rate=0.5
n_estimators=1000
max_depth=2
max_features=0.75
warm_start=True
1527498
loss=deviance
learning_rate=0.5
n_estimators=1000
max_depth=2
max_features=0.75
warm_start=True
1527499
loss=deviance
learning_rate=0.5
n_estimators=1000
max_depth=2
max_features=0.75
warm_start=True
1527500
loss=deviance
learning_rate=0.5
n_estimators=1000
max_depth=2
max_features=0.75
warm_start=True
1527501
loss=deviance
learning_rate=0.5
n_estimators=1000
max_depth=2
max_features=0.75
warm_start=True
1527502
loss=deviance
learning_rate=0.5
n_estimators=1000
max_depth=2
max_features=0.75
warm_start=True
1527503
loss=deviance
learning_rate=0.5
n_estimators=1000
max_depth=2
max_features=0.75
warm_start=True
1527504
loss=deviance
learning_rate=0.5
n_estimators=1000
max_depth=2
max_features=0.75
warm_start=True
1527505
loss=deviance
learning_rate=0.5
n_estimators=1000
max_depth=2
max_features=0.75
warm_start=True
1527506
loss=deviance
learning_rate=0.5
n_estimators=1000
max_depth=2
max_features=0.75
warm_start=True
1527507
loss=deviance
learning_rate=0.5
n_estimators=1000
max_depth=2
max_features=0.75
warm_start=True
1527508
loss=deviance
learning_rate=0.5
n_estimators=1000
max_depth=2
max_features=0.75
warm_start=True
1527509 rows × 6 columns
In [163]:
method_data1 = method_data.drop('Parameters', 1) #delete the Paameters column from the original dataframe
idx = method_param.index.get_values() #get the index of the parameter dataframe
#idx
method_data2 = method_data1.set_index(idx) #set the index of method dataframe same as parameter dataframe
#kneighbor_data2
result = pd.concat([method_data2, method_param], axis = 1) #finally add the parameter columns to get the result (desired format)
#result
In [164]:
import os
if not os.path.isdir('HPCC_benchmark_results'):
os.mkdir('HPCC_benchmark_results')
result.to_pickle('HPCC_benchmark_results/GradientBoostingClassifier-hpcc_results.tsv.gz')
In [165]:
data = pd.read_pickle('HPCC_benchmark_results/GradientBoostingClassifier-hpcc_results.tsv.gz')
data
Out[165]:
Dataset_Name
Method_Name
Test_Score
Param1
Param2
Param3
Param4
Param5
Param6
0
heart-c
GradientBoostingClassifier
0.736842
loss=exponential
learning_rate=10.0
n_estimators=100
max_depth=3
max_features=sqrt
warm_start=True
1
heart-c
GradientBoostingClassifier
0.815789
loss=exponential
learning_rate=10.0
n_estimators=100
max_depth=3
max_features=sqrt
warm_start=True
2
heart-c
GradientBoostingClassifier
0.802632
loss=exponential
learning_rate=10.0
n_estimators=100
max_depth=3
max_features=sqrt
warm_start=True
3
heart-c
GradientBoostingClassifier
0.750000
loss=exponential
learning_rate=10.0
n_estimators=100
max_depth=3
max_features=sqrt
warm_start=True
4
heart-c
GradientBoostingClassifier
0.815789
loss=exponential
learning_rate=10.0
n_estimators=100
max_depth=3
max_features=sqrt
warm_start=True
5
heart-c
GradientBoostingClassifier
0.684211
loss=exponential
learning_rate=10.0
n_estimators=100
max_depth=3
max_features=sqrt
warm_start=True
6
heart-c
GradientBoostingClassifier
0.763158
loss=exponential
learning_rate=10.0
n_estimators=100
max_depth=3
max_features=sqrt
warm_start=True
7
heart-c
GradientBoostingClassifier
0.750000
loss=exponential
learning_rate=10.0
n_estimators=100
max_depth=3
max_features=sqrt
warm_start=True
8
heart-c
GradientBoostingClassifier
0.710526
loss=exponential
learning_rate=10.0
n_estimators=100
max_depth=3
max_features=sqrt
warm_start=True
9
heart-c
GradientBoostingClassifier
0.776316
loss=exponential
learning_rate=10.0
n_estimators=100
max_depth=3
max_features=sqrt
warm_start=True
10
heart-c
GradientBoostingClassifier
0.723684
loss=exponential
learning_rate=10.0
n_estimators=100
max_depth=3
max_features=sqrt
warm_start=True
11
heart-c
GradientBoostingClassifier
0.736842
loss=exponential
learning_rate=10.0
n_estimators=100
max_depth=3
max_features=sqrt
warm_start=True
12
heart-c
GradientBoostingClassifier
0.789474
loss=exponential
learning_rate=10.0
n_estimators=100
max_depth=3
max_features=sqrt
warm_start=True
13
heart-c
GradientBoostingClassifier
0.789474
loss=exponential
learning_rate=10.0
n_estimators=100
max_depth=3
max_features=sqrt
warm_start=True
14
heart-c
GradientBoostingClassifier
0.736842
loss=exponential
learning_rate=10.0
n_estimators=100
max_depth=3
max_features=sqrt
warm_start=True
15
heart-c
GradientBoostingClassifier
0.736842
loss=exponential
learning_rate=10.0
n_estimators=100
max_depth=3
max_features=sqrt
warm_start=True
16
heart-c
GradientBoostingClassifier
0.776316
loss=exponential
learning_rate=10.0
n_estimators=100
max_depth=3
max_features=sqrt
warm_start=True
17
heart-c
GradientBoostingClassifier
0.763158
loss=exponential
learning_rate=10.0
n_estimators=100
max_depth=3
max_features=sqrt
warm_start=True
18
heart-c
GradientBoostingClassifier
0.802632
loss=exponential
learning_rate=10.0
n_estimators=100
max_depth=3
max_features=sqrt
warm_start=True
19
heart-c
GradientBoostingClassifier
0.815789
loss=exponential
learning_rate=10.0
n_estimators=100
max_depth=3
max_features=sqrt
warm_start=True
20
heart-c
GradientBoostingClassifier
0.828947
loss=exponential
learning_rate=10.0
n_estimators=100
max_depth=3
max_features=sqrt
warm_start=True
21
heart-c
GradientBoostingClassifier
0.736842
loss=exponential
learning_rate=10.0
n_estimators=100
max_depth=3
max_features=sqrt
warm_start=True
22
heart-c
GradientBoostingClassifier
0.736842
loss=exponential
learning_rate=10.0
n_estimators=100
max_depth=3
max_features=sqrt
warm_start=True
23
heart-c
GradientBoostingClassifier
0.750000
loss=exponential
learning_rate=10.0
n_estimators=100
max_depth=3
max_features=sqrt
warm_start=True
24
heart-c
GradientBoostingClassifier
0.789474
loss=exponential
learning_rate=10.0
n_estimators=100
max_depth=3
max_features=sqrt
warm_start=True
25
heart-c
GradientBoostingClassifier
0.815789
loss=exponential
learning_rate=10.0
n_estimators=100
max_depth=3
max_features=sqrt
warm_start=True
26
heart-c
GradientBoostingClassifier
0.697368
loss=exponential
learning_rate=10.0
n_estimators=100
max_depth=3
max_features=sqrt
warm_start=True
27
heart-c
GradientBoostingClassifier
0.842105
loss=exponential
learning_rate=10.0
n_estimators=100
max_depth=3
max_features=sqrt
warm_start=True
28
heart-c
GradientBoostingClassifier
0.776316
loss=exponential
learning_rate=10.0
n_estimators=100
max_depth=3
max_features=sqrt
warm_start=True
29
shuttle-landing-control
GradientBoostingClassifier
0.750000
loss=deviance
learning_rate=50.0
n_estimators=10
max_depth=2
max_features=log2
warm_start=True
...
...
...
...
...
...
...
...
...
...
1527479
shuttle-landing-control
GradientBoostingClassifier
0.500000
loss=deviance
learning_rate=0.5
n_estimators=1000
max_depth=2
max_features=0.75
warm_start=True
1527480
shuttle-landing-control
GradientBoostingClassifier
0.750000
loss=deviance
learning_rate=0.5
n_estimators=1000
max_depth=2
max_features=0.75
warm_start=True
1527481
shuttle-landing-control
GradientBoostingClassifier
0.750000
loss=deviance
learning_rate=0.5
n_estimators=1000
max_depth=2
max_features=0.75
warm_start=True
1527482
shuttle-landing-control
GradientBoostingClassifier
0.500000
loss=deviance
learning_rate=0.5
n_estimators=1000
max_depth=2
max_features=0.75
warm_start=True
1527483
shuttle-landing-control
GradientBoostingClassifier
0.750000
loss=deviance
learning_rate=0.5
n_estimators=1000
max_depth=2
max_features=0.75
warm_start=True
1527484
shuttle-landing-control
GradientBoostingClassifier
0.750000
loss=deviance
learning_rate=0.5
n_estimators=1000
max_depth=2
max_features=0.75
warm_start=True
1527485
shuttle-landing-control
GradientBoostingClassifier
0.750000
loss=deviance
learning_rate=0.5
n_estimators=1000
max_depth=2
max_features=0.75
warm_start=True
1527486
shuttle-landing-control
GradientBoostingClassifier
0.250000
loss=deviance
learning_rate=0.5
n_estimators=1000
max_depth=2
max_features=0.75
warm_start=True
1527487
shuttle-landing-control
GradientBoostingClassifier
0.750000
loss=deviance
learning_rate=0.5
n_estimators=1000
max_depth=2
max_features=0.75
warm_start=True
1527488
shuttle-landing-control
GradientBoostingClassifier
0.750000
loss=deviance
learning_rate=0.5
n_estimators=1000
max_depth=2
max_features=0.75
warm_start=True
1527489
shuttle-landing-control
GradientBoostingClassifier
1.000000
loss=deviance
learning_rate=0.5
n_estimators=1000
max_depth=2
max_features=0.75
warm_start=True
1527490
shuttle-landing-control
GradientBoostingClassifier
0.500000
loss=deviance
learning_rate=0.5
n_estimators=1000
max_depth=2
max_features=0.75
warm_start=True
1527491
shuttle-landing-control
GradientBoostingClassifier
1.000000
loss=deviance
learning_rate=0.5
n_estimators=1000
max_depth=2
max_features=0.75
warm_start=True
1527492
shuttle-landing-control
GradientBoostingClassifier
0.750000
loss=deviance
learning_rate=0.5
n_estimators=1000
max_depth=2
max_features=0.75
warm_start=True
1527493
shuttle-landing-control
GradientBoostingClassifier
0.750000
loss=deviance
learning_rate=0.5
n_estimators=1000
max_depth=2
max_features=0.75
warm_start=True
1527494
shuttle-landing-control
GradientBoostingClassifier
0.750000
loss=deviance
learning_rate=0.5
n_estimators=1000
max_depth=2
max_features=0.75
warm_start=True
1527495
shuttle-landing-control
GradientBoostingClassifier
0.750000
loss=deviance
learning_rate=0.5
n_estimators=1000
max_depth=2
max_features=0.75
warm_start=True
1527496
shuttle-landing-control
GradientBoostingClassifier
0.750000
loss=deviance
learning_rate=0.5
n_estimators=1000
max_depth=2
max_features=0.75
warm_start=True
1527497
shuttle-landing-control
GradientBoostingClassifier
0.500000
loss=deviance
learning_rate=0.5
n_estimators=1000
max_depth=2
max_features=0.75
warm_start=True
1527498
shuttle-landing-control
GradientBoostingClassifier
0.500000
loss=deviance
learning_rate=0.5
n_estimators=1000
max_depth=2
max_features=0.75
warm_start=True
1527499
shuttle-landing-control
GradientBoostingClassifier
0.500000
loss=deviance
learning_rate=0.5
n_estimators=1000
max_depth=2
max_features=0.75
warm_start=True
1527500
shuttle-landing-control
GradientBoostingClassifier
0.500000
loss=deviance
learning_rate=0.5
n_estimators=1000
max_depth=2
max_features=0.75
warm_start=True
1527501
shuttle-landing-control
GradientBoostingClassifier
0.750000
loss=deviance
learning_rate=0.5
n_estimators=1000
max_depth=2
max_features=0.75
warm_start=True
1527502
shuttle-landing-control
GradientBoostingClassifier
0.750000
loss=deviance
learning_rate=0.5
n_estimators=1000
max_depth=2
max_features=0.75
warm_start=True
1527503
shuttle-landing-control
GradientBoostingClassifier
1.000000
loss=deviance
learning_rate=0.5
n_estimators=1000
max_depth=2
max_features=0.75
warm_start=True
1527504
shuttle-landing-control
GradientBoostingClassifier
0.500000
loss=deviance
learning_rate=0.5
n_estimators=1000
max_depth=2
max_features=0.75
warm_start=True
1527505
shuttle-landing-control
GradientBoostingClassifier
0.500000
loss=deviance
learning_rate=0.5
n_estimators=1000
max_depth=2
max_features=0.75
warm_start=True
1527506
shuttle-landing-control
GradientBoostingClassifier
0.500000
loss=deviance
learning_rate=0.5
n_estimators=1000
max_depth=2
max_features=0.75
warm_start=True
1527507
shuttle-landing-control
GradientBoostingClassifier
0.250000
loss=deviance
learning_rate=0.5
n_estimators=1000
max_depth=2
max_features=0.75
warm_start=True
1527508
shuttle-landing-control
GradientBoostingClassifier
0.500000
loss=deviance
learning_rate=0.5
n_estimators=1000
max_depth=2
max_features=0.75
warm_start=True
1527509 rows × 9 columns
Content source: rhiever/sklearn-benchmarks
Similar notebooks: