10093632
1
Jan van Rijn
9976
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)
8018746
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
7
8783
min_samples_split
16
8783
min_weight_fraction_leaf
0.0
8783
presort
false
8783
random_state
8472
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.
1485
madelon
https://www.openml.org/data/download/1590986/phpfLuQE4
-1
21107801
description
https://api.openml.org/data/download/21107801/description.xml
-1
21107802
predictions
https://api.openml.org/data/download/21107802/predictions.arff
area_under_roc_curve
0.8132860946745561 [0.813286,0.813286]
average_cost
0
f_measure
0.7692295402756583 [0.768697,0.769762]
kappa
0.5384615384615385
kb_relative_information_score
1375.9030742281861
mean_absolute_error
0.23673042769196614
mean_prior_absolute_error
0.5
number_of_instances
2600 [1300,1300]
precision
0.7692365044462486 [0.770479,0.767994]
predictive_accuracy
0.7692307692307692
prior_entropy
1
recall
0.7692307692307693 [0.766923,0.771538]
relative_absolute_error
0.47346085538393223
root_mean_prior_squared_error
0.5
root_mean_squared_error
0.44172671781654144
root_relative_squared_error
0.8834534356330829
total_cost
0
area_under_roc_curve
0.8747633136094675 [0.874763,0.874763]
area_under_roc_curve
0.8175443786982248 [0.817544,0.817544]
area_under_roc_curve
0.798284023668639 [0.798284,0.798284]
area_under_roc_curve
0.8289349112426035 [0.828935,0.828935]
area_under_roc_curve
0.8076627218934911 [0.807663,0.807663]
area_under_roc_curve
0.8237278106508876 [0.823728,0.823728]
area_under_roc_curve
0.785680473372781 [0.78568,0.78568]
area_under_roc_curve
0.7527514792899408 [0.752751,0.752751]
area_under_roc_curve
0.8064497041420118 [0.80645,0.80645]
area_under_roc_curve
0.8329289940828403 [0.832929,0.832929]
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
0.8306088604596067 [0.825397,0.835821]
f_measure
0.7499667115444363 [0.752852,0.747082]
f_measure
0.7497000844206816 [0.741036,0.758364]
f_measure
0.7921108742004264 [0.785714,0.798507]
f_measure
0.7921970280030785 [0.796992,0.787402]
f_measure
0.7960784313725489 [0.792157,0.8]
f_measure
0.7191268960414353 [0.724528,0.713725]
f_measure
0.696149351321765 [0.697318,0.694981]
f_measure
0.7806102056224186 [0.786517,0.774704]
f_measure
0.7846026392094209 [0.78626,0.782946]
kappa
0.6615384615384616
kappa
0.5
kappa
0.5
kappa
0.5846153846153845
kappa
0.5846153846153845
kappa
0.5923076923076922
kappa
0.43846153846153846
kappa
0.39230769230769225
kappa
0.5615384615384615
kappa
0.5692307692307692
kb_relative_information_score
169.2545544079927
kb_relative_information_score
133.09370259993426
kb_relative_information_score
128.38654152866127
kb_relative_information_score
147.91373051536567
kb_relative_information_score
141.66269417269197
kb_relative_information_score
144.0911716595084
kb_relative_information_score
120.2196958201254
kb_relative_information_score
105.55574326671203
kb_relative_information_score
138.97538415786067
kb_relative_information_score
146.7498560993322
mean_absolute_error
0.1760650353919584
mean_absolute_error
0.24303806236498549
mean_absolute_error
0.2548450374411913
mean_absolute_error
0.21718446083830706
mean_absolute_error
0.23121501361885985
mean_absolute_error
0.22539505366428444
mean_absolute_error
0.2679061003099465
mean_absolute_error
0.2969927188196419
mean_absolute_error
0.23518452701145015
mean_absolute_error
0.21947826745903676
mean_prior_absolute_error
0.5
mean_prior_absolute_error
0.5
mean_prior_absolute_error
0.5
mean_prior_absolute_error
0.5
mean_prior_absolute_error
0.5
mean_prior_absolute_error
0.5
mean_prior_absolute_error
0.5
mean_prior_absolute_error
0.5
mean_prior_absolute_error
0.5
mean_prior_absolute_error
0.5
number_of_instances
260 [130,130]
number_of_instances
260 [130,130]
number_of_instances
260 [130,130]
number_of_instances
260 [130,130]
number_of_instances
260 [130,130]
number_of_instances
260 [130,130]
number_of_instances
260 [130,130]
number_of_instances
260 [130,130]
number_of_instances
260 [130,130]
number_of_instances
260 [130,130]
precision
0.8320266096459967 [0.852459,0.811594]
precision
0.7501332070333313 [0.744361,0.755906]
precision
0.7512039954813009 [0.768595,0.733813]
precision
0.7934188643383226 [0.811475,0.775362]
precision
0.7929316888045541 [0.779412,0.806452]
precision
0.7965925925925926 [0.808,0.785185]
precision
0.7195555555555555 [0.711111,0.728]
precision
0.6961654535771347 [0.694656,0.697674]
precision
0.7815856625719542 [0.766423,0.796748]
precision
0.7846827651515151 [0.780303,0.789062]
predictive_accuracy
0.8307692307692308
predictive_accuracy
0.75
predictive_accuracy
0.75
predictive_accuracy
0.7923076923076923
predictive_accuracy
0.7923076923076923
predictive_accuracy
0.7961538461538461
predictive_accuracy
0.7192307692307692
predictive_accuracy
0.6961538461538461
predictive_accuracy
0.7807692307692308
predictive_accuracy
0.7846153846153847
prior_entropy
1
prior_entropy
1
prior_entropy
1
prior_entropy
1
prior_entropy
1
prior_entropy
1
prior_entropy
1
prior_entropy
1
prior_entropy
1
prior_entropy
1
recall
0.8307692307692308 [0.8,0.861538]
recall
0.75 [0.761538,0.738462]
recall
0.75 [0.715385,0.784615]
recall
0.7923076923076923 [0.761538,0.823077]
recall
0.7923076923076923 [0.815385,0.769231]
recall
0.7961538461538461 [0.776923,0.815385]
recall
0.7192307692307692 [0.738462,0.7]
recall
0.6961538461538461 [0.7,0.692308]
recall
0.7807692307692308 [0.807692,0.753846]
recall
0.7846153846153846 [0.792308,0.776923]
relative_absolute_error
0.3521300707839168
relative_absolute_error
0.48607612472997097
relative_absolute_error
0.5096900748823826
relative_absolute_error
0.4343689216766141
relative_absolute_error
0.46243002723771975
relative_absolute_error
0.4507901073285689
relative_absolute_error
0.535812200619893
relative_absolute_error
0.5939854376392838
relative_absolute_error
0.4703690540229003
relative_absolute_error
0.4389565349180735
root_mean_prior_squared_error
0.5
root_mean_prior_squared_error
0.5
root_mean_prior_squared_error
0.5
root_mean_prior_squared_error
0.5
root_mean_prior_squared_error
0.5
root_mean_prior_squared_error
0.5
root_mean_prior_squared_error
0.5
root_mean_prior_squared_error
0.5
root_mean_prior_squared_error
0.5
root_mean_prior_squared_error
0.5
root_mean_squared_error
0.37589819676724184
root_mean_squared_error
0.4465050421519521
root_mean_squared_error
0.4530665313885269
root_mean_squared_error
0.424992045399015
root_mean_squared_error
0.4366505942751246
root_mean_squared_error
0.4278735067839117
root_mean_squared_error
0.4735282399455398
root_mean_squared_error
0.4997876089558506
root_mean_squared_error
0.4483310532033681
root_mean_squared_error
0.41942143980291013
root_relative_squared_error
0.7517963935344837
root_relative_squared_error
0.8930100843039042
root_relative_squared_error
0.9061330627770539
root_relative_squared_error
0.84998409079803
root_relative_squared_error
0.8733011885502492
root_relative_squared_error
0.8557470135678232
root_relative_squared_error
0.9470564798910796
root_relative_squared_error
0.9995752179117012
root_relative_squared_error
0.8966621064067362
root_relative_squared_error
0.8388428796058203
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
1014.7963890012761
usercpu_time_millis
941.860702001577
usercpu_time_millis
993.2217400018999
usercpu_time_millis
933.5409479972441
usercpu_time_millis
942.3483280006621
usercpu_time_millis
962.6925939992361
usercpu_time_millis
1002.6243219981552
usercpu_time_millis
1079.1713369981153
usercpu_time_millis
968.5756279977795
usercpu_time_millis
973.0436210011248
usercpu_time_millis_testing
5.370085000322433
usercpu_time_millis_testing
5.267378001008183
usercpu_time_millis_testing
5.262345999653917
usercpu_time_millis_testing
5.164453999896068
usercpu_time_millis_testing
5.219398000917863
usercpu_time_millis_testing
5.200527000852162
usercpu_time_millis_testing
5.218800997681683
usercpu_time_millis_testing
5.16732699907152
usercpu_time_millis_testing
5.238358000497101
usercpu_time_millis_testing
5.237319001025753
usercpu_time_millis_training
1009.4263040009537
usercpu_time_millis_training
936.5933240005688
usercpu_time_millis_training
987.959394002246
usercpu_time_millis_training
928.376493997348
usercpu_time_millis_training
937.1289299997443
usercpu_time_millis_training
957.492066998384
usercpu_time_millis_training
997.4055210004735
usercpu_time_millis_training
1074.0040099990438
usercpu_time_millis_training
963.3372699972824
usercpu_time_millis_training
967.8063020000991