10153029
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)
8078694
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
"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
10
8783
min_samples_split
11
8783
min_weight_fraction_leaf
0.0
8783
presort
false
8783
random_state
27575
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
21226597
description
https://api.openml.org/data/download/21226597/description.xml
-1
21226598
predictions
https://api.openml.org/data/download/21226598/predictions.arff
area_under_roc_curve
0.93180375 [0.991724,0.883893,0.970237,0.937993,0.923051,0.950243,0.853418,0.975799,0.975136,0.856543]
average_cost
0
f_measure
0.7644913063833804 [0.962406,0.692494,0.908629,0.809756,0.71066,0.842377,0.509615,0.833333,0.935323,0.440318]
kappa
0.7388888888888889
kb_relative_information_score
1535.7827727032009
mean_absolute_error
0.054422021768221716
mean_prior_absolute_error
0.18000000000000554
number_of_instances
2000 [200,200,200,200,200,200,200,200,200,200]
precision
0.7650317520372215 [0.964824,0.671362,0.92268,0.790476,0.721649,0.871658,0.490741,0.817308,0.930693,0.468927]
predictive_accuracy
0.765
prior_entropy
3.321928094887362
recall
0.765 [0.96,0.715,0.895,0.83,0.7,0.815,0.53,0.85,0.94,0.415]
relative_absolute_error
0.30234456537900023
root_mean_prior_squared_error
0.3000000000000046
root_mean_squared_error
0.1901404114404126
root_relative_squared_error
0.6338013714680324
total_cost
0
area_under_roc_curve
0.9431666666666666 [0.999861,0.942083,0.992222,0.939583,0.955556,0.995278,0.808333,0.990694,0.998333,0.809722]
area_under_roc_curve
0.9057638888888888 [0.971528,0.915,0.919722,0.906667,0.823333,0.894167,0.86375,0.989444,0.948333,0.825694]
area_under_roc_curve
0.9342638888888888 [0.999583,0.874444,0.945417,0.902639,0.985694,0.993194,0.883333,0.943056,0.999861,0.815417]
area_under_roc_curve
0.9207777777777778 [0.973889,0.86625,0.994028,0.983472,0.944167,0.879028,0.792639,0.968472,0.949167,0.856667]
area_under_roc_curve
0.9248194444444444 [1,0.841111,0.946528,0.940972,0.928611,0.945833,0.874861,0.928611,0.996806,0.844861]
area_under_roc_curve
0.9398611111111111 [1,0.914444,0.998611,0.940417,0.924028,0.936111,0.853056,0.986667,0.998194,0.847083]
area_under_roc_curve
0.9482222222222222 [0.999583,0.895556,0.947639,0.912639,0.975556,0.983472,0.946389,0.985417,0.974444,0.861528]
area_under_roc_curve
0.9193888888888889 [0.974444,0.818472,0.996944,0.923333,0.845694,0.989583,0.834861,0.985694,0.920278,0.904583]
area_under_roc_curve
0.958777777777778 [0.999722,0.891806,0.998056,0.988056,0.953472,0.917222,0.913056,0.988333,0.999722,0.938333]
area_under_roc_curve
0.9234444444444446 [1,0.879583,0.962917,0.941111,0.900972,0.969722,0.761389,0.99375,0.969583,0.855417]
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
0.7497275442028704 [0.97561,0.682927,0.9,0.820513,0.731707,0.923077,0.418605,0.820513,0.9,0.324324]
f_measure
0.7307764841364864 [0.923077,0.697674,0.864865,0.780488,0.585366,0.684211,0.487805,0.871795,0.947368,0.465116]
f_measure
0.7445658101145906 [0.974359,0.666667,0.918919,0.769231,0.791667,0.857143,0.5,0.777778,0.97561,0.214286]
f_measure
0.7854730046611346 [0.974359,0.666667,0.95,0.851064,0.711111,0.777778,0.578947,0.833333,0.947368,0.564103]
f_measure
0.7494632608788128 [0.97561,0.564103,0.894737,0.8,0.685714,0.9,0.511628,0.782609,0.930233,0.45]
f_measure
0.7417876547896708 [1,0.711111,0.95,0.837209,0.647059,0.8,0.30303,0.818182,0.930233,0.421053]
f_measure
0.8141471442434215 [0.974359,0.780488,0.923077,0.810811,0.769231,0.829268,0.714286,0.863636,0.95,0.526316]
f_measure
0.7690216919661782 [0.95,0.65,0.930233,0.727273,0.709677,0.95,0.512821,0.837209,0.864865,0.55814]
f_measure
0.7909709274339645 [0.947368,0.736842,0.871795,0.844444,0.780488,0.764706,0.622222,0.909091,0.97561,0.457143]
f_measure
0.7485836007645423 [0.930233,0.761905,0.878049,0.85,0.666667,0.918919,0.409091,0.810811,0.926829,0.333333]
kappa
0.7222222222222222
kappa
0.6944444444444444
kappa
0.7277777777777777
kappa
0.7611111111111112
kappa
0.7222222222222222
kappa
0.7277777777777777
kappa
0.7944444444444444
kappa
0.7444444444444445
kappa
0.7722222222222223
kappa
0.7222222222222222
kb_relative_information_score
152.57109105945673
kb_relative_information_score
144.6299202700278
kb_relative_information_score
154.216174038698
kb_relative_information_score
153.14852479753415
kb_relative_information_score
153.32876768599107
kb_relative_information_score
151.7011350022051
kb_relative_information_score
158.91267236996336
kb_relative_information_score
151.8984795903434
kb_relative_information_score
162.2453333403067
kb_relative_information_score
153.130674548696
mean_absolute_error
0.054656270913469036
mean_absolute_error
0.06289681106647045
mean_absolute_error
0.05378762307953483
mean_absolute_error
0.05449610018464508
mean_absolute_error
0.05452817268730579
mean_absolute_error
0.05595733507118952
mean_absolute_error
0.04936977010347751
mean_absolute_error
0.05526459877841455
mean_absolute_error
0.04675218579150463
mean_absolute_error
0.056511350006202915
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
0.750915780499843 [0.952381,0.666667,0.9,0.842105,0.714286,0.947368,0.391304,0.842105,0.9,0.352941]
precision
0.740198428723129 [0.947368,0.652174,0.941176,0.761905,0.571429,0.722222,0.47619,0.894737,1,0.434783]
precision
0.755354294827979 [1,0.636364,1,0.789474,0.678571,0.818182,0.428571,0.875,0.952381,0.375]
precision
0.796966285663654 [1,0.636364,0.95,0.740741,0.64,0.875,0.611111,0.9375,1,0.578947]
precision
0.7599239877843997 [0.952381,0.578947,0.944444,0.933333,0.8,0.9,0.478261,0.692308,0.869565,0.45]
precision
0.7406948027817593 [1,0.64,0.95,0.782609,0.785714,0.8,0.384615,0.75,0.869565,0.444444]
precision
0.8169664021908605 [1,0.761905,0.947368,0.882353,0.789474,0.809524,0.681818,0.791667,0.95,0.555556]
precision
0.7858071970206848 [0.95,0.65,0.869565,0.666667,1,0.95,0.526316,0.782609,0.941176,0.521739]
precision
0.8002038429406849 [1,0.777778,0.894737,0.76,0.761905,0.928571,0.56,0.833333,0.952381,0.533333]
precision
0.7525306174061055 [0.869565,0.727273,0.857143,0.85,0.684211,1,0.375,0.882353,0.904762,0.375]
predictive_accuracy
0.75
predictive_accuracy
0.725
predictive_accuracy
0.755
predictive_accuracy
0.785
predictive_accuracy
0.75
predictive_accuracy
0.755
predictive_accuracy
0.815
predictive_accuracy
0.77
predictive_accuracy
0.795
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
0.75 [1,0.7,0.9,0.8,0.75,0.9,0.45,0.8,0.9,0.3]
recall
0.725 [0.9,0.75,0.8,0.8,0.6,0.65,0.5,0.85,0.9,0.5]
recall
0.755 [0.95,0.7,0.85,0.75,0.95,0.9,0.6,0.7,1,0.15]
recall
0.785 [0.95,0.7,0.95,1,0.8,0.7,0.55,0.75,0.9,0.55]
recall
0.75 [1,0.55,0.85,0.7,0.6,0.9,0.55,0.9,1,0.45]
recall
0.755 [1,0.8,0.95,0.9,0.55,0.8,0.25,0.9,1,0.4]
recall
0.815 [0.95,0.8,0.9,0.75,0.75,0.85,0.75,0.95,0.95,0.5]
recall
0.77 [0.95,0.65,1,0.8,0.55,0.95,0.5,0.9,0.8,0.6]
recall
0.795 [0.9,0.7,0.85,0.95,0.8,0.65,0.7,1,1,0.4]
recall
0.75 [1,0.8,0.9,0.85,0.65,0.85,0.45,0.75,0.95,0.3]
relative_absolute_error
0.30364594951927276
relative_absolute_error
0.34942672814705844
relative_absolute_error
0.2988201282196383
relative_absolute_error
0.30275611213691744
relative_absolute_error
0.3029342927072547
relative_absolute_error
0.310874083728831
relative_absolute_error
0.27427650057487535
relative_absolute_error
0.3070255487689701
relative_absolute_error
0.2597343655083593
relative_absolute_error
0.3139519444789054
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
0.19283102441208627
root_mean_squared_error
0.21026476824800003
root_mean_squared_error
0.18800254214658255
root_mean_squared_error
0.19124249725580467
root_mean_squared_error
0.19306940955712687
root_mean_squared_error
0.19057878612418852
root_mean_squared_error
0.17760623922548402
root_mean_squared_error
0.19455568850396987
root_mean_squared_error
0.16772200510314186
root_mean_squared_error
0.19260685738228664
root_relative_squared_error
0.6427700813736213
root_relative_squared_error
0.7008825608266672
root_relative_squared_error
0.626675140488609
root_relative_squared_error
0.6374749908526826
root_relative_squared_error
0.6435646985237566
root_relative_squared_error
0.6352626204139621
root_relative_squared_error
0.5920207974182804
root_relative_squared_error
0.6485189616798999
root_relative_squared_error
0.5590733503438066
root_relative_squared_error
0.6420228579409559
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
691.9782569984818
usercpu_time_millis
494.5453330001328
usercpu_time_millis
470.95287399861263
usercpu_time_millis
465.0270240017562
usercpu_time_millis
467.3484449976968
usercpu_time_millis
463.44275400042534
usercpu_time_millis
487.7711589997489
usercpu_time_millis
493.19139100043685
usercpu_time_millis
462.22109900008945
usercpu_time_millis
465.6830499989155
usercpu_time_millis_testing
1.8515979991207132
usercpu_time_millis_testing
1.3315390006027883
usercpu_time_millis_testing
1.3305309985298663
usercpu_time_millis_testing
1.328427000771626
usercpu_time_millis_testing
1.321464998909505
usercpu_time_millis_testing
1.3301119997777278
usercpu_time_millis_testing
1.3308670004335
usercpu_time_millis_testing
1.3394710003922228
usercpu_time_millis_testing
1.3298590001795674
usercpu_time_millis_testing
1.3301740000315476
usercpu_time_millis_training
690.1266589993611
usercpu_time_millis_training
493.21379399953
usercpu_time_millis_training
469.62234300008276
usercpu_time_millis_training
463.6985970009846
usercpu_time_millis_training
466.0269799987873
usercpu_time_millis_training
462.1126420006476
usercpu_time_millis_training
486.4402919993154
usercpu_time_millis_training
491.85192000004463
usercpu_time_millis_training
460.8912399999099
usercpu_time_millis_training
464.352875998884