10093001
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)
8018112
axis
0
8778
copy
true
8778
missing_values
"NaN"
8778
strategy
"median"
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
3
8783
min_samples_split
2
8783
min_weight_fraction_leaf
0.0
8783
presort
false
8783
random_state
58811
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
21106539
description
https://api.openml.org/data/download/21106539/description.xml
-1
21106540
predictions
https://api.openml.org/data/download/21106540/predictions.arff
area_under_roc_curve
0.8854590277777777 [0.994933,0.841226,0.937901,0.907965,0.83645,0.921657,0.752571,0.939385,0.970193,0.752308]
average_cost
0
f_measure
0.7408491425856732 [0.967901,0.655087,0.869347,0.779904,0.641604,0.82199,0.473815,0.790932,0.938776,0.469136]
kappa
0.7111111111111111
kb_relative_information_score
1495.294247827505
mean_absolute_error
0.05296333333333371
mean_prior_absolute_error
0.18000000000000554
number_of_instances
2000 [200,200,200,200,200,200,200,200,200,200]
precision
0.7424980203310309 [0.956098,0.650246,0.873737,0.747706,0.643216,0.862637,0.472637,0.796954,0.958333,0.463415]
predictive_accuracy
0.74
prior_entropy
3.321928094887362
recall
0.74 [0.98,0.66,0.865,0.815,0.64,0.785,0.475,0.785,0.92,0.475]
relative_absolute_error
0.29424074074073375
root_mean_prior_squared_error
0.3000000000000046
root_mean_squared_error
0.21096715120816611
root_relative_squared_error
0.703223837360543
total_cost
0
area_under_roc_curve
0.8964166666666665 [1,0.935694,0.920833,0.946667,0.833472,0.974444,0.734722,0.88625,0.974444,0.757639]
area_under_roc_curve
0.8830972222222222 [0.974722,0.874306,0.870139,0.897222,0.750972,0.905278,0.806389,0.964167,0.974306,0.813472]
area_under_roc_curve
0.8601805555555555 [1,0.857917,0.924167,0.835833,0.87875,0.894583,0.6225,0.917361,0.997222,0.673472]
area_under_roc_curve
0.8987361111111111 [1,0.780556,0.971528,0.973889,0.905972,0.945694,0.723194,0.887222,0.974861,0.824444]
area_under_roc_curve
0.8745 [1,0.775833,0.974444,0.912222,0.827361,0.855,0.765278,0.925694,0.969167,0.74]
area_under_roc_curve
0.9124861111111109 [1,0.896111,0.99625,0.886667,0.88625,0.946111,0.835972,0.961944,0.997083,0.718472]
area_under_roc_curve
0.88275 [0.999722,0.827222,0.872222,0.914306,0.823472,0.911806,0.785833,0.985972,0.999306,0.707639]
area_under_roc_curve
0.878013888888889 [0.974861,0.862639,0.920417,0.879167,0.77375,0.9425,0.776944,0.939167,0.894306,0.816389]
area_under_roc_curve
0.8946805555555557 [1,0.789167,0.967083,0.969722,0.825972,0.919306,0.753056,0.960833,1,0.761667]
area_under_roc_curve
0.873013888888889 [1,0.811111,0.962639,0.863056,0.850139,0.921667,0.726111,0.965139,0.91875,0.711528]
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
0.7459306176636088 [0.97561,0.755556,0.755556,0.842105,0.684211,0.974359,0.428571,0.685714,0.947368,0.410256]
f_measure
0.7147737670048557 [0.926829,0.652174,0.833333,0.842105,0.512821,0.648649,0.418605,0.829268,0.947368,0.536585]
f_measure
0.7138948998512541 [1,0.666667,0.894737,0.682927,0.731707,0.8,0.311111,0.742857,0.97561,0.333333]
f_measure
0.7764285398327953 [1,0.6,0.923077,0.904762,0.638298,0.871795,0.571429,0.756757,0.974359,0.52381]
f_measure
0.708275754544189 [0.952381,0.5625,0.95,0.790698,0.6,0.65,0.461538,0.727273,0.926829,0.461538]
f_measure
0.7835248761912346 [0.97561,0.8,0.926829,0.744186,0.722222,0.9,0.55814,0.837209,0.95,0.421053]
f_measure
0.7261935697921011 [0.923077,0.619048,0.833333,0.75,0.578947,0.8,0.52381,0.883721,0.95,0.4]
f_measure
0.728909249231033 [0.95,0.595745,0.842105,0.711111,0.615385,0.9,0.564103,0.705882,0.833333,0.571429]
f_measure
0.7488295614303779 [1,0.611111,0.857143,0.808511,0.65,0.8,0.4375,0.790698,1,0.533333]
f_measure
0.757388836494428 [0.97561,0.684211,0.883721,0.731707,0.682927,0.864865,0.487805,0.904762,0.871795,0.486486]
kappa
0.7166666666666667
kappa
0.6777777777777777
kappa
0.6722222222222222
kappa
0.75
kappa
0.6833333333333333
kappa
0.7611111111111112
kappa
0.6944444444444444
kappa
0.6944444444444444
kappa
0.7277777777777777
kappa
0.7333333333333334
kb_relative_information_score
153.37739780996333
kb_relative_information_score
147.64297027170647
kb_relative_information_score
142.48978661521653
kb_relative_information_score
153.97896769415766
kb_relative_information_score
144.878970338549
kb_relative_information_score
159.54963770843258
kb_relative_information_score
147.3296065409687
kb_relative_information_score
145.6995178260406
kb_relative_information_score
153.00209149300488
kb_relative_information_score
147.34530152949523
mean_absolute_error
0.04905
mean_absolute_error
0.054983333333333315
mean_absolute_error
0.05861666666666661
mean_absolute_error
0.04948333333333333
mean_absolute_error
0.05726666666666664
mean_absolute_error
0.04296666666666668
mean_absolute_error
0.0561
mean_absolute_error
0.0571833333333333
mean_absolute_error
0.04931666666666667
mean_absolute_error
0.054666666666666634
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
0.755363560416192 [0.952381,0.68,0.68,0.888889,0.722222,1,0.409091,0.8,1,0.421053]
precision
0.7264909694148153 [0.904762,0.576923,0.9375,0.888889,0.526316,0.705882,0.391304,0.809524,1,0.52381]
precision
0.7312323232323233 [1,0.636364,0.944444,0.666667,0.714286,0.933333,0.28,0.866667,0.952381,0.318182]
precision
0.7851493260781186 [1,0.6,0.947368,0.863636,0.555556,0.894737,0.666667,0.823529,1,0.5]
precision
0.7117018336354721 [0.909091,0.75,0.95,0.73913,0.6,0.65,0.473684,0.666667,0.904762,0.473684]
precision
0.7897420634920636 [0.952381,0.933333,0.904762,0.695652,0.8125,0.9,0.521739,0.782609,0.95,0.444444]
precision
0.7312975579594573 [0.947368,0.590909,0.9375,0.75,0.611111,0.8,0.5,0.826087,0.95,0.4]
precision
0.7448031125794283 [0.95,0.518519,0.888889,0.64,0.631579,0.9,0.578947,0.857143,0.9375,0.545455]
precision
0.7595182623334797 [1,0.6875,0.818182,0.703704,0.65,0.933333,0.583333,0.73913,1,0.48]
precision
0.7586794429303515 [0.952381,0.722222,0.826087,0.714286,0.666667,0.941176,0.47619,0.863636,0.894737,0.529412]
predictive_accuracy
0.745
predictive_accuracy
0.71
predictive_accuracy
0.705
predictive_accuracy
0.775
predictive_accuracy
0.715
predictive_accuracy
0.785
predictive_accuracy
0.725
predictive_accuracy
0.725
predictive_accuracy
0.755
predictive_accuracy
0.76
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
0.745 [1,0.85,0.85,0.8,0.65,0.95,0.45,0.6,0.9,0.4]
recall
0.71 [0.95,0.75,0.75,0.8,0.5,0.6,0.45,0.85,0.9,0.55]
recall
0.705 [1,0.7,0.85,0.7,0.75,0.7,0.35,0.65,1,0.35]
recall
0.775 [1,0.6,0.9,0.95,0.75,0.85,0.5,0.7,0.95,0.55]
recall
0.715 [1,0.45,0.95,0.85,0.6,0.65,0.45,0.8,0.95,0.45]
recall
0.785 [1,0.7,0.95,0.8,0.65,0.9,0.6,0.9,0.95,0.4]
recall
0.725 [0.9,0.65,0.75,0.75,0.55,0.8,0.55,0.95,0.95,0.4]
recall
0.725 [0.95,0.7,0.8,0.8,0.6,0.9,0.55,0.6,0.75,0.6]
recall
0.755 [1,0.55,0.9,0.95,0.65,0.7,0.35,0.85,1,0.6]
recall
0.76 [1,0.65,0.95,0.75,0.7,0.8,0.5,0.95,0.85,0.45]
relative_absolute_error
0.2725000000000003
relative_absolute_error
0.3054629629629632
relative_absolute_error
0.3256481481481482
relative_absolute_error
0.2749074074074077
relative_absolute_error
0.31814814814814835
relative_absolute_error
0.23870370370370403
relative_absolute_error
0.311666666666667
relative_absolute_error
0.31768518518518535
relative_absolute_error
0.27398148148148177
relative_absolute_error
0.30370370370370386
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
0.20034414834922878
root_mean_squared_error
0.2143186879392462
root_mean_squared_error
0.22878786875376253
root_mean_squared_error
0.2020588473137907
root_mean_squared_error
0.22097888285233647
root_mean_squared_error
0.1889054731281701
root_mean_squared_error
0.21533049533733536
root_mean_squared_error
0.21907951372351847
root_mean_squared_error
0.20313241439459578
root_mean_squared_error
0.21374439563802988
root_relative_squared_error
0.6678138278307629
root_relative_squared_error
0.7143956264641544
root_relative_squared_error
0.762626229179209
root_relative_squared_error
0.6735294910459693
root_relative_squared_error
0.7365962761744553
root_relative_squared_error
0.629684910427234
root_relative_squared_error
0.7177683177911183
root_relative_squared_error
0.7302650457450619
root_relative_squared_error
0.6771080479819864
root_relative_squared_error
0.7124813187934333
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
194.5319570004358
usercpu_time_millis
178.53521600045497
usercpu_time_millis
177.34938800003874
usercpu_time_millis
192.491470999812
usercpu_time_millis
133.74725499943452
usercpu_time_millis
134.45336799941288
usercpu_time_millis
134.1769220007336
usercpu_time_millis
130.41782100026467
usercpu_time_millis
131.52495700069267
usercpu_time_millis
128.07922399952076
usercpu_time_millis_testing
1.8485280006643734
usercpu_time_millis_testing
1.8094220004059025
usercpu_time_millis_testing
1.8032790003417176
usercpu_time_millis_testing
1.822088999688276
usercpu_time_millis_testing
1.3028109997321735
usercpu_time_millis_testing
1.403600999765331
usercpu_time_millis_testing
1.6594230000919197
usercpu_time_millis_testing
1.3104769996061805
usercpu_time_millis_testing
1.3149450005585095
usercpu_time_millis_testing
1.307386000007682
usercpu_time_millis_training
192.68342899977142
usercpu_time_millis_training
176.72579400004906
usercpu_time_millis_training
175.54610899969703
usercpu_time_millis_training
190.66938200012373
usercpu_time_millis_training
132.44444399970234
usercpu_time_millis_training
133.04976699964755
usercpu_time_millis_training
132.5174990006417
usercpu_time_millis_training
129.1073440006585
usercpu_time_millis_training
130.21001200013416
usercpu_time_millis_training
126.77183799951308