10126270
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)
8051682
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
"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
13
8783
min_samples_split
14
8783
min_weight_fraction_leaf
0.0
8783
presort
false
8783
random_state
1417
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
21173078
description
https://api.openml.org/data/download/21173078/description.xml
-1
21173079
predictions
https://api.openml.org/data/download/21173079/predictions.arff
area_under_roc_curve
0.9394093055555557 [0.994044,0.906711,0.966867,0.945375,0.915125,0.951063,0.889494,0.971358,0.980225,0.873831]
average_cost
0
f_measure
0.7528573732658161 [0.955665,0.672897,0.895288,0.769976,0.688442,0.829016,0.495,0.835749,0.937343,0.449198]
kappa
0.7266666666666667
kb_relative_information_score
1527.8917090229133
mean_absolute_error
0.057470397416657
mean_prior_absolute_error
0.18000000000000554
number_of_instances
2000 [200,200,200,200,200,200,200,200,200,200]
precision
0.7537368406771701 [0.941748,0.631579,0.93956,0.746479,0.691919,0.860215,0.495,0.808411,0.939698,0.482759]
predictive_accuracy
0.754
prior_entropy
3.321928094887362
recall
0.754 [0.97,0.72,0.855,0.795,0.685,0.8,0.495,0.865,0.935,0.42]
relative_absolute_error
0.31927998564808463
root_mean_prior_squared_error
0.3000000000000046
root_mean_squared_error
0.18907647049606305
root_relative_squared_error
0.6302549016535338
total_cost
0
area_under_roc_curve
0.9441666666666666 [1,0.965556,0.964444,0.933194,0.931944,0.997083,0.855139,0.967917,0.9975,0.828889]
area_under_roc_curve
0.9094027777777778 [0.974444,0.912778,0.917639,0.930556,0.81875,0.896667,0.841389,0.988056,0.948333,0.865417]
area_under_roc_curve
0.934888888888889 [0.998889,0.898472,0.945139,0.869167,0.972222,0.989583,0.901667,0.945972,0.999722,0.828056]
area_under_roc_curve
0.9266111111111112 [0.997361,0.861111,0.971806,0.987778,0.910417,0.879444,0.835694,0.939722,0.974583,0.908194]
area_under_roc_curve
0.9375000000000003 [0.996944,0.901111,0.966111,0.934444,0.922639,0.967639,0.924722,0.929167,0.996528,0.835694]
area_under_roc_curve
0.9512638888888888 [1,0.944444,0.998472,0.962778,0.934167,0.935833,0.891111,0.988194,0.99875,0.858889]
area_under_roc_curve
0.9513194444444444 [0.999722,0.893472,0.9475,0.960694,0.954722,0.978194,0.94375,0.986806,0.974306,0.874028]
area_under_roc_curve
0.9416666666666668 [0.973472,0.911667,0.999444,0.940417,0.858889,0.993611,0.921528,0.989444,0.946389,0.881806]
area_under_roc_curve
0.9675 [0.999722,0.892083,0.998333,0.991944,0.956806,0.9425,0.960139,0.990556,1,0.942917]
area_under_roc_curve
0.933111111111111 [1,0.892222,0.963611,0.941667,0.895972,0.937917,0.821111,0.9925,0.969306,0.916806]
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
0.7450919594226393 [0.97561,0.652174,0.842105,0.820513,0.790698,0.923077,0.47619,0.789474,0.878049,0.30303]
f_measure
0.6984005747217751 [0.974359,0.697674,0.833333,0.780488,0.585366,0.648649,0.1875,0.829268,0.947368,0.5]
f_measure
0.7328552095521478 [0.95,0.638298,0.918919,0.666667,0.755556,0.878049,0.409091,0.833333,0.97561,0.30303]
f_measure
0.7655152374416008 [0.904762,0.651163,0.923077,0.826087,0.634146,0.777778,0.585366,0.810811,0.947368,0.594595]
f_measure
0.7080861660191409 [0.97561,0.595745,0.888889,0.702703,0.619048,0.842105,0.363636,0.727273,0.97561,0.390244]
f_measure
0.7749359065411768 [0.97561,0.782609,0.947368,0.837209,0.628571,0.857143,0.484848,0.790698,0.904762,0.540541]
f_measure
0.7810601303458446 [0.974359,0.666667,0.923077,0.761905,0.75,0.761905,0.734694,0.863636,0.974359,0.4]
f_measure
0.7537603366673133 [0.95,0.651163,0.9,0.651163,0.628571,0.9,0.564103,0.863636,0.864865,0.564103]
f_measure
0.8025867780160449 [0.95,0.702703,0.894737,0.826087,0.8,0.823529,0.585366,0.888889,0.97561,0.578947]
f_measure
0.7389099817175219 [0.930233,0.7,0.878049,0.8,0.666667,0.864865,0.434783,0.952381,0.926829,0.235294]
kappa
0.7222222222222222
kappa
0.6666666666666666
kappa
0.7055555555555556
kappa
0.7388888888888889
kappa
0.6777777777777777
kappa
0.7611111111111112
kappa
0.7666666666666667
kappa
0.7277777777777777
kappa
0.7833333333333334
kappa
0.7166666666666667
kb_relative_information_score
154.3700400536099
kb_relative_information_score
143.3567101202949
kb_relative_information_score
149.5831550569152
kb_relative_information_score
152.78667194199016
kb_relative_information_score
149.14957798504415
kb_relative_information_score
155.0943336338638
kb_relative_information_score
157.74153332895793
kb_relative_information_score
151.72790052688612
kb_relative_information_score
163.9649049430146
kb_relative_information_score
150.1168814323537
mean_absolute_error
0.0541800585620837
mean_absolute_error
0.06669528558592354
mean_absolute_error
0.06047213760391202
mean_absolute_error
0.0560604488777476
mean_absolute_error
0.06135862851544735
mean_absolute_error
0.055661662603523177
mean_absolute_error
0.052844084578655484
mean_absolute_error
0.06039531780830403
mean_absolute_error
0.0475723485610499
mean_absolute_error
0.05946400146991849
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
0.7476434066823083 [0.952381,0.576923,0.888889,0.842105,0.73913,0.947368,0.454545,0.833333,0.857143,0.384615]
precision
0.7094663408841798 [1,0.652174,0.9375,0.761905,0.571429,0.705882,0.25,0.809524,1,0.40625]
precision
0.7442194749694748 [0.95,0.555556,1,0.75,0.68,0.857143,0.375,0.9375,0.952381,0.384615]
precision
0.7745357622814211 [0.863636,0.608696,0.947368,0.730769,0.619048,0.875,0.571429,0.882353,1,0.647059]
precision
0.7176941794588854 [0.952381,0.518519,1,0.764706,0.590909,0.888889,0.461538,0.666667,0.952381,0.380952]
precision
0.7785199199777204 [0.952381,0.692308,1,0.782609,0.733333,0.818182,0.615385,0.73913,0.863636,0.588235]
precision
0.7914270197437167 [1,0.75,0.947368,0.727273,0.75,0.727273,0.62069,0.791667,1,0.6]
precision
0.7591462511778166 [0.95,0.608696,0.9,0.608696,0.733333,0.9,0.578947,0.791667,0.941176,0.578947]
precision
0.8124840192487252 [0.95,0.764706,0.944444,0.730769,0.8,1,0.571429,0.8,0.952381,0.611111]
precision
0.7402067029304882 [0.869565,0.7,0.857143,0.8,0.75,0.941176,0.384615,0.909091,0.904762,0.285714]
predictive_accuracy
0.75
predictive_accuracy
0.7
predictive_accuracy
0.735
predictive_accuracy
0.765
predictive_accuracy
0.71
predictive_accuracy
0.785
predictive_accuracy
0.79
predictive_accuracy
0.755
predictive_accuracy
0.805
predictive_accuracy
0.745
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 [1,0.75,0.8,0.8,0.85,0.9,0.5,0.75,0.9,0.25]
recall
0.7 [0.95,0.75,0.75,0.8,0.6,0.6,0.15,0.85,0.9,0.65]
recall
0.735 [0.95,0.75,0.85,0.6,0.85,0.9,0.45,0.75,1,0.25]
recall
0.765 [0.95,0.7,0.9,0.95,0.65,0.7,0.6,0.75,0.9,0.55]
recall
0.71 [1,0.7,0.8,0.65,0.65,0.8,0.3,0.8,1,0.4]
recall
0.785 [1,0.9,0.9,0.9,0.55,0.9,0.4,0.85,0.95,0.5]
recall
0.79 [0.95,0.6,0.9,0.8,0.75,0.8,0.9,0.95,0.95,0.3]
recall
0.755 [0.95,0.7,0.9,0.7,0.55,0.9,0.55,0.95,0.8,0.55]
recall
0.805 [0.95,0.65,0.85,0.95,0.8,0.7,0.6,1,1,0.55]
recall
0.745 [1,0.7,0.9,0.8,0.6,0.8,0.5,1,0.95,0.2]
relative_absolute_error
0.3010003253449098
relative_absolute_error
0.3705293643662423
relative_absolute_error
0.3359563200217338
relative_absolute_error
0.31144693820970926
relative_absolute_error
0.3408812695302634
relative_absolute_error
0.30923145890846243
relative_absolute_error
0.29357824765919743
relative_absolute_error
0.3355295433794672
relative_absolute_error
0.2642908253391664
relative_absolute_error
0.3303555637217698
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
0.1885605687575288
root_mean_squared_error
0.2114442826014611
root_mean_squared_error
0.19313190635728192
root_mean_squared_error
0.19052704156872657
root_mean_squared_error
0.19798313669421566
root_mean_squared_error
0.1802384802058278
root_mean_squared_error
0.1781791639661352
root_mean_squared_error
0.18861354259721222
root_mean_squared_error
0.1619023284223039
root_mean_squared_error
0.19600096520643986
root_relative_squared_error
0.6285352291917631
root_relative_squared_error
0.704814275338204
root_relative_squared_error
0.6437730211909402
root_relative_squared_error
0.6350901385624222
root_relative_squared_error
0.6599437889807193
root_relative_squared_error
0.6007949340194263
root_relative_squared_error
0.5939305465537843
root_relative_squared_error
0.6287118086573744
root_relative_squared_error
0.5396744280743466
root_relative_squared_error
0.6533365506881332
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
2559.9632630000997
usercpu_time_millis
2397.2084950000863
usercpu_time_millis
2402.5658469981863
usercpu_time_millis
2387.78643799742
usercpu_time_millis
2398.0489790010324
usercpu_time_millis
2394.2203520018666
usercpu_time_millis
2420.3106700006174
usercpu_time_millis
2431.500791997678
usercpu_time_millis
2425.377388000925
usercpu_time_millis
2414.640164002776
usercpu_time_millis_testing
1.7130870000983123
usercpu_time_millis_testing
1.6916450003918726
usercpu_time_millis_testing
1.6762749983172398
usercpu_time_millis_testing
1.6285469973809086
usercpu_time_millis_testing
1.746537000144599
usercpu_time_millis_testing
1.6881000010471325
usercpu_time_millis_testing
1.6896320012165233
usercpu_time_millis_testing
1.701623998087598
usercpu_time_millis_testing
1.6456390003440902
usercpu_time_millis_testing
1.5578470010950696
usercpu_time_millis_training
2558.2501760000014
usercpu_time_millis_training
2395.5168499996944
usercpu_time_millis_training
2400.889571999869
usercpu_time_millis_training
2386.157891000039
usercpu_time_millis_training
2396.302442000888
usercpu_time_millis_training
2392.5322520008194
usercpu_time_millis_training
2418.621037999401
usercpu_time_millis_training
2429.7991679995903
usercpu_time_millis_training
2423.7317490005807
usercpu_time_millis_training
2413.082317001681