10065892
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)
7990735
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
"gini"
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
12
8783
min_samples_split
15
8783
min_weight_fraction_leaf
0.0
8783
presort
false
8783
random_state
35320
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
21052319
description
https://api.openml.org/data/download/21052319/description.xml
-1
21052320
predictions
https://api.openml.org/data/download/21052320/predictions.arff
area_under_roc_curve
0.9288230555555557 [0.994321,0.903446,0.944837,0.942992,0.872324,0.950011,0.861287,0.960213,0.983126,0.875674]
average_cost
0
f_measure
0.7379560625515615 [0.975369,0.660832,0.880407,0.790576,0.645161,0.791045,0.496487,0.77561,0.934726,0.429348]
kappa
0.7083333333333334
kb_relative_information_score
1477.5814821555934
mean_absolute_error
0.06128901667758005
mean_prior_absolute_error
0.18000000000000554
number_of_instances
2000 [200,200,200,200,200,200,200,200,200,200]
precision
0.7432043586123663 [0.961165,0.587549,0.896373,0.82967,0.697674,0.787129,0.46696,0.757143,0.978142,0.470238]
predictive_accuracy
0.7375
prior_entropy
3.321928094887362
recall
0.7375 [0.99,0.755,0.865,0.755,0.6,0.795,0.53,0.795,0.895,0.395]
relative_absolute_error
0.3404945370976565
root_mean_prior_squared_error
0.3000000000000046
root_mean_squared_error
0.19581166024478683
root_relative_squared_error
0.6527055341492795
total_cost
0
area_under_roc_curve
0.9395555555555556 [0.996667,0.960694,0.914028,0.940139,0.901389,0.996667,0.864444,0.929444,0.997222,0.894861]
area_under_roc_curve
0.9250833333333334 [0.974444,0.914028,0.883194,0.987083,0.799722,0.957222,0.914028,0.951389,0.946944,0.922778]
area_under_roc_curve
0.9075277777777778 [1,0.879444,0.959167,0.907778,0.864306,0.940556,0.773611,0.899444,0.997083,0.853889]
area_under_roc_curve
0.9368749999999999 [1,0.837778,0.969583,0.982917,0.934306,0.917222,0.87875,0.982083,0.974583,0.891528]
area_under_roc_curve
0.9312638888888888 [0.999167,0.888194,0.969722,0.9825,0.910417,0.881806,0.880972,0.982222,0.971806,0.845833]
area_under_roc_curve
0.9452916666666666 [0.999722,0.927917,0.998611,0.911806,0.888889,0.963194,0.837361,0.98875,0.995833,0.940833]
area_under_roc_curve
0.9164166666666667 [0.999583,0.961111,0.864583,0.903056,0.833056,0.925278,0.914167,0.958333,0.996806,0.808194]
area_under_roc_curve
0.9327916666666667 [0.974861,0.930278,0.937361,0.90625,0.863056,0.989028,0.899722,0.995,0.952639,0.879722]
area_under_roc_curve
0.9375000000000001 [1,0.844861,0.99625,0.981111,0.875139,0.960417,0.849167,0.983889,1,0.884167]
area_under_roc_curve
0.9191666666666669 [0.999444,0.902361,0.960833,0.926111,0.865278,0.970139,0.804861,0.936389,0.982361,0.843889]
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
0.7254468603180851 [0.97561,0.641509,0.829268,0.833333,0.648649,0.894737,0.478261,0.702703,0.947368,0.30303]
f_measure
0.7328635389249772 [0.926829,0.717949,0.8,0.790698,0.685714,0.8,0.439024,0.8,0.947368,0.421053]
f_measure
0.6651425190027446 [1,0.54902,0.888889,0.702703,0.608696,0.789474,0.391304,0.451613,0.97561,0.294118]
f_measure
0.7506091339273857 [1,0.608696,0.883721,0.780488,0.684211,0.764706,0.590909,0.731707,0.947368,0.514286]
f_measure
0.7173017482330257 [0.97561,0.619048,0.894737,0.820513,0.628571,0.697674,0.410256,0.755556,0.95,0.421053]
f_measure
0.7675149808280815 [0.97561,0.8,0.952381,0.764706,0.7,0.837209,0.521739,0.863636,0.947368,0.3125]
f_measure
0.7501438305832799 [0.97561,0.64,0.833333,0.789474,0.647059,0.666667,0.681818,0.790698,0.947368,0.529412]
f_measure
0.7578818169479272 [0.974359,0.625,0.894737,0.809524,0.594595,0.820513,0.585366,0.904762,0.857143,0.512821]
f_measure
0.7641478272303418 [1,0.736842,0.952381,0.810811,0.588235,0.761905,0.4,0.826087,1,0.565217]
f_measure
0.7342147232930288 [0.952381,0.72,0.864865,0.8,0.666667,0.894737,0.444444,0.829268,0.810811,0.358974]
kappa
0.6944444444444444
kappa
0.7055555555555556
kappa
0.6277777777777779
kappa
0.7222222222222222
kappa
0.6888888888888889
kappa
0.75
kappa
0.7222222222222222
kappa
0.7277777777777777
kappa
0.7444444444444445
kappa
0.7
kb_relative_information_score
148.46434427267886
kb_relative_information_score
146.0123917804069
kb_relative_information_score
140.592230367436
kb_relative_information_score
152.0054929558278
kb_relative_information_score
148.12933328354515
kb_relative_information_score
152.80585220783016
kb_relative_information_score
149.1640229702209
kb_relative_information_score
147.71490176672958
kb_relative_information_score
153.00630979361517
kb_relative_information_score
139.6866027573212
mean_absolute_error
0.05978474534712081
mean_absolute_error
0.06379443739207499
mean_absolute_error
0.06689545155828297
mean_absolute_error
0.056214153858136905
mean_absolute_error
0.06012968665583083
mean_absolute_error
0.058272148113324575
mean_absolute_error
0.05970444326560052
mean_absolute_error
0.06148581531127971
mean_absolute_error
0.05692366419587947
mean_absolute_error
0.06968562107826808
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
0.7437281264487146 [0.952381,0.515152,0.809524,0.9375,0.705882,0.944444,0.423077,0.764706,1,0.384615]
precision
0.7373750317823543 [0.904762,0.736842,0.8,0.73913,0.8,0.72,0.428571,0.8,1,0.444444]
precision
0.6880154949414912 [1,0.451613,1,0.764706,0.538462,0.833333,0.346154,0.636364,0.952381,0.357143]
precision
0.7633199288634072 [1,0.538462,0.826087,0.761905,0.722222,0.928571,0.541667,0.714286,1,0.6]
precision
0.7210844073292586 [0.952381,0.590909,0.944444,0.842105,0.733333,0.652174,0.421053,0.68,0.95,0.444444]
precision
0.774252378056726 [0.952381,0.8,0.909091,0.928571,0.7,0.782609,0.461538,0.791667,1,0.416667]
precision
0.7685613118765293 [0.952381,0.533333,0.9375,0.833333,0.785714,0.636364,0.625,0.73913,1,0.642857]
precision
0.7703430814111928 [1,0.535714,0.944444,0.772727,0.647059,0.842105,0.571429,0.863636,1,0.526316]
precision
0.7708215967039496 [1,0.777778,0.909091,0.882353,0.714286,0.727273,0.466667,0.730769,1,0.5]
precision
0.7538342960788782 [0.909091,0.6,0.941176,0.933333,0.75,0.944444,0.4,0.809524,0.882353,0.368421]
predictive_accuracy
0.725
predictive_accuracy
0.735
predictive_accuracy
0.665
predictive_accuracy
0.75
predictive_accuracy
0.72
predictive_accuracy
0.775
predictive_accuracy
0.75
predictive_accuracy
0.755
predictive_accuracy
0.77
predictive_accuracy
0.73
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
0.725 [1,0.85,0.85,0.75,0.6,0.85,0.55,0.65,0.9,0.25]
recall
0.735 [0.95,0.7,0.8,0.85,0.6,0.9,0.45,0.8,0.9,0.4]
recall
0.665 [1,0.7,0.8,0.65,0.7,0.75,0.45,0.35,1,0.25]
recall
0.75 [1,0.7,0.95,0.8,0.65,0.65,0.65,0.75,0.9,0.45]
recall
0.72 [1,0.65,0.85,0.8,0.55,0.75,0.4,0.85,0.95,0.4]
recall
0.775 [1,0.8,1,0.65,0.7,0.9,0.6,0.95,0.9,0.25]
recall
0.75 [1,0.8,0.75,0.75,0.55,0.7,0.75,0.85,0.9,0.45]
recall
0.755 [0.95,0.75,0.85,0.85,0.55,0.8,0.6,0.95,0.75,0.5]
recall
0.77 [1,0.7,1,0.75,0.5,0.8,0.35,0.95,1,0.65]
recall
0.73 [1,0.9,0.8,0.7,0.6,0.85,0.5,0.85,0.75,0.35]
relative_absolute_error
0.3321374741506715
relative_absolute_error
0.35441354106708367
relative_absolute_error
0.37164139754601694
relative_absolute_error
0.3123008547674276
relative_absolute_error
0.3340538147546161
relative_absolute_error
0.3237341561851369
relative_absolute_error
0.3316913514755588
relative_absolute_error
0.34158786284044323
relative_absolute_error
0.31624257886599744
relative_absolute_error
0.38714233932371195
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
0.1955494130708672
root_mean_squared_error
0.20056241738227015
root_mean_squared_error
0.21134437259973118
root_mean_squared_error
0.18784897229186404
root_mean_squared_error
0.19850991680885338
root_mean_squared_error
0.18255798720280053
root_mean_squared_error
0.19525357407155589
root_mean_squared_error
0.19264854744602844
root_mean_squared_error
0.18445328046800824
root_mean_squared_error
0.20738728741113116
root_relative_squared_error
0.6518313769028912
root_relative_squared_error
0.6685413912742342
root_relative_squared_error
0.7044812419991043
root_relative_squared_error
0.6261632409728805
root_relative_squared_error
0.6616997226961785
root_relative_squared_error
0.6085266240093355
root_relative_squared_error
0.6508452469051866
root_relative_squared_error
0.6421618248200951
root_relative_squared_error
0.6148442682266945
root_relative_squared_error
0.6912909580371043
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
2549.59597099878
usercpu_time_millis
2260.8419400003186
usercpu_time_millis
2361.700765999558
usercpu_time_millis
2426.375814999119
usercpu_time_millis
2461.5282049999223
usercpu_time_millis
2437.8405589977774
usercpu_time_millis
2446.454231001553
usercpu_time_millis
2457.6802299998235
usercpu_time_millis
2773.569799001052
usercpu_time_millis
2697.5124850014254
usercpu_time_millis_testing
1.3999709990457632
usercpu_time_millis_testing
1.3753900002484443
usercpu_time_millis_testing
1.6364579987566685
usercpu_time_millis_testing
1.7368899989378406
usercpu_time_millis_testing
1.6407940001954557
usercpu_time_millis_testing
1.7437689984944882
usercpu_time_millis_testing
1.5473000003112247
usercpu_time_millis_testing
1.557719999254914
usercpu_time_millis_testing
1.7254040012630867
usercpu_time_millis_testing
1.4794230010011233
usercpu_time_millis_training
2548.1959999997343
usercpu_time_millis_training
2259.46655000007
usercpu_time_millis_training
2360.0643080008012
usercpu_time_millis_training
2424.638925000181
usercpu_time_millis_training
2459.887410999727
usercpu_time_millis_training
2436.096789999283
usercpu_time_millis_training
2444.906931001242
usercpu_time_millis_training
2456.1225100005686
usercpu_time_millis_training
2771.844394999789
usercpu_time_millis_training
2696.0330620004243