10093792
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)
8018906
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
14
8783
min_samples_split
9
8783
min_weight_fraction_leaf
0.0
8783
presort
false
8783
random_state
41146
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
21108121
description
https://api.openml.org/data/download/21108121/description.xml
-1
21108122
predictions
https://api.openml.org/data/download/21108122/predictions.arff
area_under_roc_curve
0.933483611111111 [0.994307,0.904899,0.947519,0.944126,0.882567,0.959824,0.867076,0.963472,0.985171,0.885875]
average_cost
0
f_measure
0.7332074905848832 [0.975369,0.64877,0.883249,0.785146,0.626632,0.781955,0.483721,0.78744,0.934726,0.425068]
kappa
0.7027777777777778
kb_relative_information_score
1462.6000509651467
mean_absolute_error
0.06310436190249584
mean_prior_absolute_error
0.18000000000000554
number_of_instances
2000 [200,200,200,200,200,200,200,200,200,200]
precision
0.7379996395250207 [0.961165,0.587045,0.896907,0.836158,0.655738,0.78392,0.452174,0.761682,0.978142,0.467066]
predictive_accuracy
0.7325
prior_entropy
3.321928094887362
recall
0.7325 [0.99,0.725,0.87,0.74,0.6,0.78,0.52,0.815,0.895,0.39]
relative_absolute_error
0.35057978834718834
root_mean_prior_squared_error
0.3000000000000046
root_mean_squared_error
0.19704553083686283
root_relative_squared_error
0.656818436122866
total_cost
0
area_under_roc_curve
0.9393888888888889 [0.996528,0.94125,0.912361,0.934306,0.928472,0.996667,0.84,0.953472,0.996389,0.894444]
area_under_roc_curve
0.9223472222222222 [0.974444,0.913889,0.882083,0.986389,0.850972,0.931667,0.867778,0.955694,0.946944,0.913611]
area_under_roc_curve
0.9033333333333334 [1,0.875,0.96125,0.908056,0.878056,0.937778,0.792917,0.830278,0.997083,0.852917]
area_under_roc_curve
0.9448611111111113 [1,0.848333,0.969722,0.983472,0.934028,0.990833,0.885417,0.980139,0.973194,0.883472]
area_under_roc_curve
0.9573611111111114 [0.999444,0.902778,0.99625,0.974722,0.953889,0.956806,0.909722,0.985694,0.997917,0.896389]
area_under_roc_curve
0.9432361111111112 [1,0.911667,0.9975,0.88875,0.929167,0.982361,0.805556,0.988333,0.997639,0.931389]
area_under_roc_curve
0.9167222222222222 [0.999861,0.959444,0.8625,0.899583,0.789861,0.924167,0.917917,0.98,0.996667,0.837222]
area_under_roc_curve
0.9297777777777779 [0.975,0.921528,0.938889,0.935278,0.823056,0.988056,0.879583,0.990278,0.954861,0.89125]
area_under_roc_curve
0.9483055555555555 [1,0.871528,0.998056,0.980278,0.871111,0.934861,0.923333,0.982222,1,0.921667]
area_under_roc_curve
0.9316666666666668 [0.999444,0.89875,0.961944,0.958194,0.879722,0.959861,0.8425,0.992083,0.979306,0.844861]
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
0.7574599177165307 [0.97561,0.68,0.829268,0.823529,0.666667,0.871795,0.55814,0.722222,0.947368,0.5]
f_measure
0.7226329599873967 [0.926829,0.744186,0.8,0.8,0.628571,0.790698,0.530612,0.8,0.947368,0.258065]
f_measure
0.6865309936238917 [1,0.571429,0.918919,0.722222,0.608696,0.820513,0.391304,0.5625,0.97561,0.294118]
f_measure
0.7340023327802829 [1,0.585366,0.883721,0.780488,0.651163,0.777778,0.55,0.731707,0.947368,0.432432]
f_measure
0.7049616200780697 [0.97561,0.55,0.894737,0.789474,0.628571,0.714286,0.428571,0.77551,0.95,0.342857]
f_measure
0.7545163614451909 [0.97561,0.717949,0.952381,0.722222,0.65,0.837209,0.454545,0.863636,0.947368,0.424242]
f_measure
0.7299919110500441 [0.97561,0.653061,0.833333,0.789474,0.606061,0.666667,0.540541,0.8,0.947368,0.487805]
f_measure
0.7440428688059102 [0.974359,0.565217,0.894737,0.809524,0.588235,0.756757,0.5,0.909091,0.857143,0.585366]
f_measure
0.7614289444724227 [1,0.756757,0.952381,0.810811,0.628571,0.761905,0.388889,0.826087,1,0.488889]
f_measure
0.7194183150057576 [0.952381,0.679245,0.864865,0.8,0.6,0.833333,0.489796,0.810811,0.810811,0.352941]
kappa
0.7277777777777777
kappa
0.7
kappa
0.65
kappa
0.7055555555555556
kappa
0.6777777777777777
kappa
0.7333333333333334
kappa
0.7
kappa
0.7111111111111111
kappa
0.7388888888888889
kappa
0.6833333333333333
kb_relative_information_score
149.0507915420916
kb_relative_information_score
143.37606066951378
kb_relative_information_score
141.17485245456265
kb_relative_information_score
147.81442495013852
kb_relative_information_score
147.73505592791722
kb_relative_information_score
149.1174994230174
kb_relative_information_score
144.18380760984485
kb_relative_information_score
146.46055996722683
kb_relative_information_score
153.32190524460472
kb_relative_information_score
140.36509317624143
mean_absolute_error
0.05940985809757409
mean_absolute_error
0.06676974603802639
mean_absolute_error
0.06648189454769811
mean_absolute_error
0.061896158934219195
mean_absolute_error
0.06222001479518369
mean_absolute_error
0.060613783831980426
mean_absolute_error
0.06465704992625064
mean_absolute_error
0.062300848261931795
mean_absolute_error
0.05700293909307061
mean_absolute_error
0.06969132549901993
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
0.775641103747511 [0.952381,0.566667,0.809524,1,0.636364,0.894737,0.521739,0.8125,1,0.5625]
precision
0.728479007249622 [0.904762,0.695652,0.8,0.8,0.733333,0.73913,0.448276,0.8,1,0.363636]
precision
0.7081503077986744 [1,0.482759,1,0.8125,0.538462,0.842105,0.346154,0.75,0.952381,0.357143]
precision
0.7377989891608818 [1,0.571429,0.826087,0.761905,0.608696,0.875,0.55,0.714286,1,0.470588]
precision
0.7109573568194258 [0.952381,0.55,0.944444,0.833333,0.733333,0.681818,0.409091,0.655172,0.95,0.4]
precision
0.7590217534182065 [0.952381,0.736842,0.909091,0.8125,0.65,0.782609,0.416667,0.791667,1,0.538462]
precision
0.7464958599547848 [0.952381,0.551724,0.9375,0.833333,0.769231,0.636364,0.588235,0.72,1,0.47619]
precision
0.7618082081317376 [1,0.5,0.944444,0.772727,0.714286,0.823529,0.458333,0.833333,1,0.571429]
precision
0.7683848553407379 [1,0.823529,0.909091,0.882353,0.733333,0.727273,0.4375,0.730769,1,0.44]
precision
0.747362567283967 [0.909091,0.545455,0.941176,0.933333,0.6,0.9375,0.413793,0.882353,0.882353,0.428571]
predictive_accuracy
0.755
predictive_accuracy
0.73
predictive_accuracy
0.685
predictive_accuracy
0.735
predictive_accuracy
0.71
predictive_accuracy
0.76
predictive_accuracy
0.73
predictive_accuracy
0.74
predictive_accuracy
0.765
predictive_accuracy
0.715
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
0.755 [1,0.85,0.85,0.7,0.7,0.85,0.6,0.65,0.9,0.45]
recall
0.73 [0.95,0.8,0.8,0.8,0.55,0.85,0.65,0.8,0.9,0.2]
recall
0.685 [1,0.7,0.85,0.65,0.7,0.8,0.45,0.45,1,0.25]
recall
0.735 [1,0.6,0.95,0.8,0.7,0.7,0.55,0.75,0.9,0.4]
recall
0.71 [1,0.55,0.85,0.75,0.55,0.75,0.45,0.95,0.95,0.3]
recall
0.76 [1,0.7,1,0.65,0.65,0.9,0.5,0.95,0.9,0.35]
recall
0.73 [1,0.8,0.75,0.75,0.5,0.7,0.5,0.9,0.9,0.5]
recall
0.74 [0.95,0.65,0.85,0.85,0.5,0.7,0.55,1,0.75,0.6]
recall
0.765 [1,0.7,1,0.75,0.55,0.8,0.35,0.95,1,0.55]
recall
0.715 [1,0.9,0.8,0.7,0.6,0.75,0.6,0.75,0.75,0.3]
relative_absolute_error
0.3300547672087453
relative_absolute_error
0.3709430335445915
relative_absolute_error
0.36934385859832325
relative_absolute_error
0.34386754963455146
relative_absolute_error
0.345666748862132
relative_absolute_error
0.33674324351100277
relative_absolute_error
0.3592058329236151
relative_absolute_error
0.3461158236773992
relative_absolute_error
0.31668299496150376
relative_absolute_error
0.3871740305501112
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
0.19147449577707298
root_mean_squared_error
0.20668060556651532
root_mean_squared_error
0.21223105298480893
root_mean_squared_error
0.19310190759592188
root_mean_squared_error
0.19350360186772195
root_mean_squared_error
0.1882701803341725
root_mean_squared_error
0.202536249872959
root_mean_squared_error
0.19569811049797042
root_mean_squared_error
0.1792400610963254
root_mean_squared_error
0.20548650370139718
root_relative_squared_error
0.6382483192569104
root_relative_squared_error
0.6889353518883848
root_relative_squared_error
0.7074368432826968
root_relative_squared_error
0.64367302531974
root_relative_squared_error
0.6450120062257403
root_relative_squared_error
0.6275672677805754
root_relative_squared_error
0.6751208329098637
root_relative_squared_error
0.6523270349932352
root_relative_squared_error
0.597466870321085
root_relative_squared_error
0.684955012337991
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
2227.8369740006383
usercpu_time_millis
2049.436379999861
usercpu_time_millis
2000.1053639998645
usercpu_time_millis
2027.4175069998819
usercpu_time_millis
1967.8871070009336
usercpu_time_millis
1939.6451510001498
usercpu_time_millis
1995.3504160002922
usercpu_time_millis
2043.36200599937
usercpu_time_millis
2010.3130079996845
usercpu_time_millis
2011.869884000589
usercpu_time_millis_testing
1.503563999904145
usercpu_time_millis_testing
1.4608399997086963
usercpu_time_millis_testing
1.4598249999835389
usercpu_time_millis_testing
1.4257610000640852
usercpu_time_millis_testing
1.3653310006702668
usercpu_time_millis_testing
1.329740000073798
usercpu_time_millis_testing
1.4024499996594386
usercpu_time_millis_testing
1.5407749997393694
usercpu_time_millis_testing
1.6425839994553826
usercpu_time_millis_testing
1.4740500000698376
usercpu_time_millis_training
2226.333410000734
usercpu_time_millis_training
2047.9755400001523
usercpu_time_millis_training
1998.645538999881
usercpu_time_millis_training
2025.9917459998178
usercpu_time_millis_training
1966.5217760002633
usercpu_time_millis_training
1938.315411000076
usercpu_time_millis_training
1993.9479660006327
usercpu_time_millis_training
2041.8212309996306
usercpu_time_millis_training
2008.670424000229
usercpu_time_millis_training
2010.3958340005192