10097647
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)
8022795
axis
0
8778
copy
true
8778
missing_values
"NaN"
8778
strategy
"mean"
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
11
8783
min_samples_split
6
8783
min_weight_fraction_leaf
0.0
8783
presort
false
8783
random_state
35672
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
21115831
description
https://www.openml.org/data/download/21115831/description.xml
-1
21115832
predictions
https://www.openml.org/data/download/21115832/predictions.arff
area_under_roc_curve
0.9348791666666666 [0.991375,0.885554,0.967337,0.947069,0.919036,0.949718,0.86599,0.978206,0.975253,0.869253]
average_cost
0
f_measure
0.755080313020895 [0.957393,0.691765,0.898172,0.793187,0.685139,0.833333,0.470886,0.831296,0.935323,0.454308]
kappa
0.7288888888888889
kb_relative_information_score
1528.2410703737075
mean_absolute_error
0.05632734522787173
mean_prior_absolute_error
0.18000000000000554
number_of_instances
2000 [200,200,200,200,200,200,200,200,200,200]
precision
0.7554150063157254 [0.959799,0.653333,0.939891,0.772512,0.690355,0.841837,0.476923,0.813397,0.930693,0.47541]
predictive_accuracy
0.7559999999999999
prior_entropy
3.321928094887362
recall
0.756 [0.955,0.735,0.86,0.815,0.68,0.825,0.465,0.85,0.94,0.435]
relative_absolute_error
0.31292969571038887
root_mean_prior_squared_error
0.3000000000000046
root_mean_squared_error
0.19077484797694813
root_relative_squared_error
0.6359161599231506
total_cost
0
area_under_roc_curve
0.9486666666666668 [1,0.942639,0.965139,0.939167,0.933194,0.996667,0.882639,0.989583,0.997917,0.839722]
area_under_roc_curve
0.9104999999999999 [0.971389,0.915694,0.919583,0.904722,0.818611,0.894167,0.876389,0.989583,0.948056,0.866806]
area_under_roc_curve
0.9416111111111111 [0.998889,0.87375,0.945972,0.932778,0.983472,0.989861,0.888333,0.945694,0.999722,0.857639]
area_under_roc_curve
0.9290555555555556 [0.970833,0.872361,0.969028,0.986806,0.919583,0.881944,0.837639,0.99375,0.949444,0.909167]
area_under_roc_curve
0.9313749999999998 [1,0.870694,0.967222,0.938611,0.951944,0.945,0.895833,0.929306,0.996528,0.818611]
area_under_roc_curve
0.9494027777777778 [1,0.939167,0.998472,0.963333,0.938056,0.936944,0.877639,0.990417,0.999028,0.850972]
area_under_roc_curve
0.9392083333333335 [0.999583,0.895417,0.947639,0.937222,0.954028,0.983194,0.864306,0.9875,0.974306,0.848889]
area_under_roc_curve
0.924263888888889 [0.974028,0.829861,0.999444,0.925278,0.841667,0.991389,0.88375,0.98625,0.920833,0.890139]
area_under_roc_curve
0.9490694444444443 [0.999722,0.841111,0.998333,0.99125,0.95375,0.942083,0.86625,0.984583,1,0.913611]
area_under_roc_curve
0.9262638888888888 [0.999583,0.879861,0.964028,0.941944,0.898611,0.941111,0.783611,0.99375,0.969444,0.890694]
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
0.7533915367370696 [0.97561,0.723404,0.842105,0.809524,0.722222,0.923077,0.428571,0.820513,0.9,0.388889]
f_measure
0.6974408861219312 [0.894737,0.697674,0.864865,0.761905,0.571429,0.648649,0.206897,0.871795,0.947368,0.509091]
f_measure
0.7424825803494405 [0.974359,0.666667,0.918919,0.820513,0.791667,0.837209,0.454545,0.727273,0.97561,0.258065]
f_measure
0.7809941866830482 [0.923077,0.682927,0.923077,0.851064,0.711111,0.777778,0.604651,0.833333,0.947368,0.555556]
f_measure
0.7320009509255354 [0.97561,0.615385,0.888889,0.756757,0.615385,0.9,0.461538,0.765957,0.930233,0.410256]
f_measure
0.7458942592317119 [1,0.708333,0.947368,0.837209,0.647059,0.857143,0.275862,0.844444,0.909091,0.432432]
f_measure
0.7996479428315113 [0.974359,0.736842,0.923077,0.810811,0.761905,0.829268,0.622222,0.863636,0.974359,0.5]
f_measure
0.7419181123771087 [0.95,0.636364,0.9,0.578947,0.628571,0.863636,0.540541,0.837209,0.864865,0.619048]
f_measure
0.7761175016834446 [0.974359,0.684211,0.894737,0.826087,0.684211,0.756757,0.55,0.888889,0.97561,0.526316]
f_measure
0.7460206234535246 [0.930233,0.761905,0.878049,0.85,0.684211,0.918919,0.425532,0.842105,0.926829,0.242424]
kappa
0.7277777777777777
kappa
0.6666666666666666
kappa
0.7222222222222222
kappa
0.7555555555555555
kappa
0.7055555555555556
kappa
0.7388888888888889
kappa
0.7777777777777778
kappa
0.7166666666666667
kappa
0.7555555555555555
kappa
0.7222222222222222
kb_relative_information_score
154.04588623777173
kb_relative_information_score
143.23501749032098
kb_relative_information_score
154.4792929756971
kb_relative_information_score
155.07490021471253
kb_relative_information_score
153.10127578673865
kb_relative_information_score
152.81412350108496
kb_relative_information_score
156.62680083950121
kb_relative_information_score
149.76485660531992
kb_relative_information_score
156.6735519889278
kb_relative_information_score
152.4253647336529
mean_absolute_error
0.05430148550280127
mean_absolute_error
0.06548883962614607
mean_absolute_error
0.05509410409851585
mean_absolute_error
0.0538289974344541
mean_absolute_error
0.05548762434675746
mean_absolute_error
0.05690035185832393
mean_absolute_error
0.05242861656317535
mean_absolute_error
0.05900827331852869
mean_absolute_error
0.05349848484848486
mean_absolute_error
0.05723667468152762
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
0.7592191336928178 [0.952381,0.62963,0.888889,0.772727,0.8125,0.947368,0.409091,0.842105,0.9,0.4375]
precision
0.7144474629183205 [0.944444,0.652174,0.941176,0.727273,0.545455,0.705882,0.333333,0.894737,1,0.4]
precision
0.7559046293142403 [1,0.6,1,0.842105,0.678571,0.782609,0.416667,0.923077,0.952381,0.363636]
precision
0.7944861640817018 [0.947368,0.666667,0.947368,0.740741,0.64,0.875,0.565217,0.9375,1,0.625]
precision
0.7370036985045735 [0.952381,0.631579,1,0.823529,0.631579,0.9,0.473684,0.666667,0.869565,0.421053]
precision
0.7502013669763029 [1,0.607143,1,0.782609,0.785714,0.818182,0.444444,0.76,0.833333,0.470588]
precision
0.8058462343470083 [1,0.777778,0.947368,0.882353,0.727273,0.809524,0.56,0.791667,1,0.5625]
precision
0.7472373995711591 [0.95,0.583333,0.9,0.611111,0.733333,0.791667,0.588235,0.782609,0.941176,0.590909]
precision
0.7801124039359333 [1,0.722222,0.944444,0.730769,0.722222,0.823529,0.55,0.8,0.952381,0.555556]
precision
0.7497916495742584 [0.869565,0.727273,0.857143,0.85,0.722222,1,0.37037,0.888889,0.904762,0.307692]
predictive_accuracy
0.755
predictive_accuracy
0.7
predictive_accuracy
0.75
predictive_accuracy
0.78
predictive_accuracy
0.735
predictive_accuracy
0.765
predictive_accuracy
0.8
predictive_accuracy
0.745
predictive_accuracy
0.78
predictive_accuracy
0.75
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 [1,0.85,0.8,0.85,0.65,0.9,0.45,0.8,0.9,0.35]
recall
0.7 [0.85,0.75,0.8,0.8,0.6,0.6,0.15,0.85,0.9,0.7]
recall
0.75 [0.95,0.75,0.85,0.8,0.95,0.9,0.5,0.6,1,0.2]
recall
0.78 [0.9,0.7,0.9,1,0.8,0.7,0.65,0.75,0.9,0.5]
recall
0.735 [1,0.6,0.8,0.7,0.6,0.9,0.45,0.9,1,0.4]
recall
0.765 [1,0.85,0.9,0.9,0.55,0.9,0.2,0.95,1,0.4]
recall
0.8 [0.95,0.7,0.9,0.75,0.8,0.85,0.7,0.95,0.95,0.45]
recall
0.745 [0.95,0.7,0.9,0.55,0.55,0.95,0.5,0.9,0.8,0.65]
recall
0.78 [0.95,0.65,0.85,0.95,0.65,0.7,0.55,1,1,0.5]
recall
0.75 [1,0.8,0.9,0.85,0.65,0.85,0.5,0.8,0.95,0.2]
relative_absolute_error
0.3016749194600074
relative_absolute_error
0.36382688681192304
relative_absolute_error
0.3060783561028662
relative_absolute_error
0.29904998574696756
relative_absolute_error
0.30826457970420845
relative_absolute_error
0.3161130658795777
relative_absolute_error
0.29127009201764115
relative_absolute_error
0.3278237406584931
relative_absolute_error
0.2972138047138051
relative_absolute_error
0.3179815260084871
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
0.18811494093459985
root_mean_squared_error
0.21303294769457504
root_mean_squared_error
0.18504357850467745
root_mean_squared_error
0.1879922975269175
root_mean_squared_error
0.19146989639952888
root_mean_squared_error
0.18501507305215592
root_mean_squared_error
0.18337654958725624
root_mean_squared_error
0.19793311552087314
root_mean_squared_error
0.18152661237870119
root_mean_squared_error
0.1922244570313268
root_relative_squared_error
0.6270498031153332
root_relative_squared_error
0.7101098256485839
root_relative_squared_error
0.6168119283489252
root_relative_squared_error
0.6266409917563921
root_relative_squared_error
0.63823298799843
root_relative_squared_error
0.6167169101738534
root_relative_squared_error
0.6112551652908546
root_relative_squared_error
0.6597770517362441
root_relative_squared_error
0.6050887079290044
root_relative_squared_error
0.640748190104423
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
658.9756320008746
usercpu_time_millis
483.93698499967286
usercpu_time_millis
495.9958719991846
usercpu_time_millis
476.9841580018692
usercpu_time_millis
480.38546300085727
usercpu_time_millis
471.89605399762513
usercpu_time_millis
518.1287880004675
usercpu_time_millis
544.8472899988701
usercpu_time_millis
512.169816000096
usercpu_time_millis
506.64127900017775
usercpu_time_millis_testing
1.8125460010196548
usercpu_time_millis_testing
1.5340589998231735
usercpu_time_millis_testing
1.6214110000873916
usercpu_time_millis_testing
1.3546080008381978
usercpu_time_millis_testing
1.310748000832973
usercpu_time_millis_testing
1.4876859986543423
usercpu_time_millis_testing
1.4513650003209477
usercpu_time_millis_testing
1.5796179995959392
usercpu_time_millis_testing
1.3669960007973714
usercpu_time_millis_testing
1.42230399978871
usercpu_time_millis_training
657.163085999855
usercpu_time_millis_training
482.4029259998497
usercpu_time_millis_training
494.3744609990972
usercpu_time_millis_training
475.629550001031
usercpu_time_millis_training
479.0747150000243
usercpu_time_millis_training
470.4083679989708
usercpu_time_millis_training
516.6774230001465
usercpu_time_millis_training
543.2676719992742
usercpu_time_millis_training
510.80281999929866
usercpu_time_millis_training
505.21897500038904