10064290
1
Jan van Rijn
14
Supervised Classification
8815
sklearn.pipeline.Pipeline(columntransformer=sklearn.compose._column_transformer.ColumnTransformer(numeric=sklearn.pipeline.Pipeline(imputer=sklearn.preprocessing.imputation.Imputer,standardscaler=sklearn.preprocessing.data.StandardScaler),nominal=sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute.SimpleImputer,onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder)),variancethreshold=sklearn.feature_selection.variance_threshold.VarianceThreshold,decisiontreeclassifier=sklearn.tree.tree.DecisionTreeClassifier)(1)
7989118
axis
0
8778
copy
true
8778
missing_values
"NaN"
8778
strategy
"most_frequent"
8778
verbose
0
8778
copy
true
8779
with_mean
true
8779
with_std
true
8779
memory
null
8780
copy
true
8781
fill_value
-1
8781
missing_values
NaN
8781
strategy
"constant"
8781
verbose
0
8781
categorical_features
null
8782
categories
null
8782
dtype
{"oml-python:serialized_object": "type", "value": "np.float64"}
8782
handle_unknown
"ignore"
8782
n_values
null
8782
sparse
true
8782
class_weight
null
8783
criterion
"entropy"
8783
max_depth
null
8783
max_features
1.0
8783
max_leaf_nodes
null
8783
min_impurity_decrease
0.0
8783
min_impurity_split
null
8783
min_samples_leaf
13
8783
min_samples_split
6
8783
min_weight_fraction_leaf
0.0
8783
presort
false
8783
random_state
2196
8783
splitter
"best"
8783
n_jobs
null
8812
remainder
"passthrough"
8812
sparse_threshold
0.3
8812
transformer_weights
null
8812
memory
null
8813
memory
null
8815
threshold
0.0
8816
openml-python
Sklearn_0.20.0.
14
mfeat-fourier
https://www.openml.org/data/download/14/dataset_14_mfeat-fourier.arff
-1
21049115
description
https://api.openml.org/data/download/21049115/description.xml
-1
21049116
predictions
https://api.openml.org/data/download/21049116/predictions.arff
area_under_roc_curve
0.9399759722222224 [0.991196,0.901419,0.967171,0.9457,0.926078,0.95185,0.886433,0.974144,0.979704,0.876064]
average_cost
0
f_measure
0.7519916553538804 [0.955665,0.668224,0.895288,0.772947,0.688442,0.831169,0.479592,0.835749,0.937343,0.455497]
kappa
0.7255555555555556
kb_relative_information_score
1527.5077046151853
mean_absolute_error
0.05749568417039772
mean_prior_absolute_error
0.18000000000000554
number_of_instances
2000 [200,200,200,200,200,200,200,200,200,200]
precision
0.7528663621788934 [0.941748,0.627193,0.93956,0.747664,0.691919,0.864865,0.489583,0.808411,0.939698,0.478022]
predictive_accuracy
0.753
prior_entropy
3.321928094887362
recall
0.753 [0.97,0.715,0.855,0.8,0.685,0.8,0.47,0.865,0.935,0.435]
relative_absolute_error
0.31942046761331083
root_mean_prior_squared_error
0.3000000000000046
root_mean_squared_error
0.1892939100028098
root_relative_squared_error
0.6309797000093563
total_cost
0
area_under_roc_curve
0.9389444444444444 [0.996806,0.939444,0.964444,0.933194,0.931389,0.994861,0.854583,0.967917,0.9975,0.809306]
area_under_roc_curve
0.9147361111111111 [0.974444,0.911944,0.919861,0.93,0.870833,0.8975,0.840972,0.988056,0.948333,0.865417]
area_under_roc_curve
0.9410000000000001 [0.974028,0.898056,0.945139,0.870278,0.977917,0.990694,0.90625,0.94625,0.997083,0.904306]
area_under_roc_curve
0.926736111111111 [0.995,0.859306,0.971806,0.987778,0.914722,0.882639,0.835694,0.965556,0.974583,0.880278]
area_under_roc_curve
0.9421527777777778 [1,0.901667,0.966111,0.936111,0.94875,0.97,0.928194,0.929167,0.996528,0.845]
area_under_roc_curve
0.9516388888888889 [1,0.944722,0.998472,0.962778,0.935833,0.936111,0.891667,0.988194,0.99875,0.859861]
area_under_roc_curve
0.9516249999999999 [0.999722,0.893472,0.9475,0.960972,0.957361,0.977083,0.943611,0.988194,0.974306,0.874028]
area_under_roc_curve
0.9383750000000001 [0.973472,0.887917,0.999444,0.942639,0.860833,0.994028,0.916389,0.98625,0.944306,0.878472]
area_under_roc_curve
0.9618194444444444 [0.999583,0.892083,0.998333,0.991111,0.955833,0.943056,0.923333,0.990556,1,0.924306]
area_under_roc_curve
0.9357499999999999 [1,0.892222,0.962361,0.940833,0.919583,0.938472,0.821111,0.9975,0.969444,0.915972]
average_cost
0
average_cost
0
average_cost
0
average_cost
0
average_cost
0
average_cost
0
average_cost
0
average_cost
0
average_cost
0
average_cost
0
f_measure
0.7464555957862757 [0.97561,0.652174,0.842105,0.820513,0.790698,0.923077,0.45,0.789474,0.878049,0.342857]
f_measure
0.6984005747217751 [0.974359,0.697674,0.833333,0.780488,0.585366,0.648649,0.1875,0.829268,0.947368,0.5]
f_measure
0.7328552095521478 [0.95,0.638298,0.918919,0.666667,0.755556,0.878049,0.409091,0.833333,0.97561,0.30303]
f_measure
0.7608640746509032 [0.904762,0.604651,0.923077,0.826087,0.634146,0.777778,0.585366,0.810811,0.947368,0.594595]
f_measure
0.7297570874573919 [0.97561,0.595745,0.888889,0.736842,0.619048,0.864865,0.4375,0.727273,0.97561,0.47619]
f_measure
0.7749359065411768 [0.97561,0.782609,0.947368,0.837209,0.628571,0.857143,0.484848,0.790698,0.904762,0.540541]
f_measure
0.7810601303458446 [0.974359,0.666667,0.923077,0.761905,0.75,0.761905,0.734694,0.863636,0.974359,0.4]
f_measure
0.743247009080815 [0.95,0.651163,0.9,0.651163,0.628571,0.9,0.486486,0.863636,0.864865,0.536585]
f_measure
0.7871824134460834 [0.95,0.702703,0.894737,0.826087,0.8,0.823529,0.473684,0.888889,0.97561,0.536585]
f_measure
0.7389099817175219 [0.930233,0.7,0.878049,0.8,0.666667,0.864865,0.434783,0.952381,0.926829,0.235294]
kappa
0.7222222222222222
kappa
0.6666666666666666
kappa
0.7055555555555556
kappa
0.7333333333333334
kappa
0.7
kappa
0.7611111111111112
kappa
0.7666666666666667
kappa
0.7166666666666667
kappa
0.7666666666666667
kappa
0.7166666666666667
kb_relative_information_score
153.50374297961426
kb_relative_information_score
143.47996075304528
kb_relative_information_score
151.0215603280212
kb_relative_information_score
151.59360775356063
kb_relative_information_score
152.22795669705857
kb_relative_information_score
155.50387116154855
kb_relative_information_score
158.02384864467984
kb_relative_information_score
151.58107030033162
kb_relative_information_score
160.5663338333977
kb_relative_information_score
150.00575216394247
mean_absolute_error
0.055795443177468325
mean_absolute_error
0.06669528558592352
mean_absolute_error
0.05931829145006587
mean_absolute_error
0.056220516751050775
mean_absolute_error
0.05826324390006274
mean_absolute_error
0.05488500176436234
mean_absolute_error
0.052396969194040105
mean_absolute_error
0.06028762550061172
mean_absolute_error
0.050784309064314775
mean_absolute_error
0.06031015531607232
mean_prior_absolute_error
0.1799999999999998
mean_prior_absolute_error
0.1799999999999998
mean_prior_absolute_error
0.1799999999999998
mean_prior_absolute_error
0.1799999999999998
mean_prior_absolute_error
0.1799999999999998
mean_prior_absolute_error
0.1799999999999998
mean_prior_absolute_error
0.1799999999999998
mean_prior_absolute_error
0.1799999999999998
mean_prior_absolute_error
0.1799999999999998
mean_prior_absolute_error
0.1799999999999998
number_of_instances
200 [20,20,20,20,20,20,20,20,20,20]
number_of_instances
200 [20,20,20,20,20,20,20,20,20,20]
number_of_instances
200 [20,20,20,20,20,20,20,20,20,20]
number_of_instances
200 [20,20,20,20,20,20,20,20,20,20]
number_of_instances
200 [20,20,20,20,20,20,20,20,20,20]
number_of_instances
200 [20,20,20,20,20,20,20,20,20,20]
number_of_instances
200 [20,20,20,20,20,20,20,20,20,20]
number_of_instances
200 [20,20,20,20,20,20,20,20,20,20]
number_of_instances
200 [20,20,20,20,20,20,20,20,20,20]
number_of_instances
200 [20,20,20,20,20,20,20,20,20,20]
precision
0.7487273227662244 [0.952381,0.576923,0.888889,0.842105,0.73913,0.947368,0.45,0.833333,0.857143,0.4]
precision
0.7094663408841798 [1,0.652174,0.9375,0.761905,0.571429,0.705882,0.25,0.809524,1,0.40625]
precision
0.7442194749694748 [0.95,0.555556,1,0.75,0.68,0.857143,0.375,0.9375,0.952381,0.384615]
precision
0.7701879361944647 [0.863636,0.565217,0.947368,0.730769,0.619048,0.875,0.571429,0.882353,1,0.647059]
precision
0.7437689217100981 [0.952381,0.518519,1,0.777778,0.590909,0.941176,0.583333,0.666667,0.952381,0.454545]
precision
0.7785199199777204 [0.952381,0.692308,1,0.782609,0.733333,0.818182,0.615385,0.73913,0.863636,0.588235]
precision
0.7914270197437167 [1,0.75,0.947368,0.727273,0.75,0.727273,0.62069,0.791667,1,0.6]
precision
0.7486789063451468 [0.95,0.608696,0.9,0.608696,0.733333,0.9,0.529412,0.791667,0.941176,0.52381]
precision
0.7966110033757093 [0.95,0.764706,0.944444,0.730769,0.8,1,0.5,0.8,0.952381,0.52381]
precision
0.7402067029304882 [0.869565,0.7,0.857143,0.8,0.75,0.941176,0.384615,0.909091,0.904762,0.285714]
predictive_accuracy
0.75
predictive_accuracy
0.7
predictive_accuracy
0.735
predictive_accuracy
0.76
predictive_accuracy
0.73
predictive_accuracy
0.785
predictive_accuracy
0.79
predictive_accuracy
0.745
predictive_accuracy
0.79
predictive_accuracy
0.745
prior_entropy
3.321928094887362
prior_entropy
3.321928094887362
prior_entropy
3.321928094887362
prior_entropy
3.321928094887362
prior_entropy
3.321928094887362
prior_entropy
3.321928094887362
prior_entropy
3.321928094887362
prior_entropy
3.321928094887362
prior_entropy
3.321928094887362
prior_entropy
3.321928094887362
recall
0.75 [1,0.75,0.8,0.8,0.85,0.9,0.45,0.75,0.9,0.3]
recall
0.7 [0.95,0.75,0.75,0.8,0.6,0.6,0.15,0.85,0.9,0.65]
recall
0.735 [0.95,0.75,0.85,0.6,0.85,0.9,0.45,0.75,1,0.25]
recall
0.76 [0.95,0.65,0.9,0.95,0.65,0.7,0.6,0.75,0.9,0.55]
recall
0.73 [1,0.7,0.8,0.7,0.65,0.8,0.35,0.8,1,0.5]
recall
0.785 [1,0.9,0.9,0.9,0.55,0.9,0.4,0.85,0.95,0.5]
recall
0.79 [0.95,0.6,0.9,0.8,0.75,0.8,0.9,0.95,0.95,0.3]
recall
0.745 [0.95,0.7,0.9,0.7,0.55,0.9,0.45,0.95,0.8,0.55]
recall
0.79 [0.95,0.65,0.85,0.95,0.8,0.7,0.45,1,1,0.55]
recall
0.745 [1,0.7,0.9,0.8,0.6,0.8,0.5,1,0.95,0.2]
relative_absolute_error
0.30997468431926883
relative_absolute_error
0.37052936436624223
relative_absolute_error
0.32954606361147737
relative_absolute_error
0.3123362041725047
relative_absolute_error
0.32368468833368225
relative_absolute_error
0.30491667646868
relative_absolute_error
0.2910942733002231
relative_absolute_error
0.3349312527811766
relative_absolute_error
0.2821350503573046
relative_absolute_error
0.33505641842262435
root_mean_prior_squared_error
0.2999999999999998
root_mean_prior_squared_error
0.2999999999999998
root_mean_prior_squared_error
0.2999999999999998
root_mean_prior_squared_error
0.2999999999999998
root_mean_prior_squared_error
0.2999999999999998
root_mean_prior_squared_error
0.2999999999999998
root_mean_prior_squared_error
0.2999999999999998
root_mean_prior_squared_error
0.2999999999999998
root_mean_prior_squared_error
0.2999999999999998
root_mean_prior_squared_error
0.2999999999999998
root_mean_squared_error
0.19085044875492815
root_mean_squared_error
0.21054687463839133
root_mean_squared_error
0.18996556398915734
root_mean_squared_error
0.1932514482396332
root_mean_squared_error
0.19081112200936587
root_mean_squared_error
0.17936641061686961
root_mean_squared_error
0.17820303136824206
root_mean_squared_error
0.19046977999179723
root_mean_squared_error
0.17166583879035083
root_mean_squared_error
0.19506284745314934
root_relative_squared_error
0.6361681625164276
root_relative_squared_error
0.7018229154613048
root_relative_squared_error
0.6332185466305249
root_relative_squared_error
0.644171494132111
root_relative_squared_error
0.6360370733645533
root_relative_squared_error
0.5978880353895658
root_relative_squared_error
0.5940101045608072
root_relative_squared_error
0.6348992666393245
root_relative_squared_error
0.5722194626345032
root_relative_squared_error
0.6502094915104982
total_cost
0
total_cost
0
total_cost
0
total_cost
0
total_cost
0
total_cost
0
total_cost
0
total_cost
0
total_cost
0
total_cost
0
usercpu_time_millis
3038.624087000244
usercpu_time_millis
2798.595152999951
usercpu_time_millis
2838.967263000086
usercpu_time_millis
2844.2718030000833
usercpu_time_millis
2803.4274269994057
usercpu_time_millis
2827.36578299955
usercpu_time_millis
2855.9893259998717
usercpu_time_millis
2846.455896000407
usercpu_time_millis
2789.2710539999825
usercpu_time_millis
2812.1022109999103
usercpu_time_millis_testing
1.3952110002719564
usercpu_time_millis_testing
1.382132999424357
usercpu_time_millis_testing
1.3703040003747446
usercpu_time_millis_testing
1.5030620006655226
usercpu_time_millis_testing
1.50415799998882
usercpu_time_millis_testing
1.3935919996583834
usercpu_time_millis_testing
1.3868269998056348
usercpu_time_millis_testing
1.5084040005604038
usercpu_time_millis_testing
1.3870709999537212
usercpu_time_millis_testing
1.397394999912649
usercpu_time_millis_training
3037.228875999972
usercpu_time_millis_training
2797.2130200005267
usercpu_time_millis_training
2837.596958999711
usercpu_time_millis_training
2842.768740999418
usercpu_time_millis_training
2801.923268999417
usercpu_time_millis_training
2825.9721909998916
usercpu_time_millis_training
2854.602499000066
usercpu_time_millis_training
2844.9474919998465
usercpu_time_millis_training
2787.883983000029
usercpu_time_millis_training
2810.7048159999977