10147852
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)
8073477
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
1
8783
min_samples_split
19
8783
min_weight_fraction_leaf
0.0
8783
presort
false
8783
random_state
20772
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
21216243
description
https://api.openml.org/data/download/21216243/description.xml
-1
21216244
predictions
https://api.openml.org/data/download/21216244/predictions.arff
area_under_roc_curve
0.8076781065088758 [0.807678,0.807678]
average_cost
0
f_measure
0.7661526008126671 [0.765613,0.766692]
kappa
0.5323076923076924
kb_relative_information_score
1390.4480927346244
mean_absolute_error
0.23289997489940942
mean_prior_absolute_error
0.5
number_of_instances
2600 [1300,1300]
precision
0.7661595158240058 [0.767388,0.764931]
predictive_accuracy
0.7661538461538462
prior_entropy
1
recall
0.7661538461538462 [0.763846,0.768462]
relative_absolute_error
0.46579994979881884
root_mean_prior_squared_error
0.5
root_mean_squared_error
0.4506890760465503
root_relative_squared_error
0.9013781520931006
total_cost
0
area_under_roc_curve
0.8350295857988166 [0.83503,0.83503]
area_under_roc_curve
0.8423076923076923 [0.842308,0.842308]
area_under_roc_curve
0.8225147928994083 [0.822515,0.822515]
area_under_roc_curve
0.8117751479289941 [0.811775,0.811775]
area_under_roc_curve
0.8343786982248521 [0.834379,0.834379]
area_under_roc_curve
0.7839644970414201 [0.783964,0.783964]
area_under_roc_curve
0.7791420118343195 [0.779142,0.779142]
area_under_roc_curve
0.7293491124260355 [0.729349,0.729349]
area_under_roc_curve
0.8065384615384615 [0.806538,0.806538]
area_under_roc_curve
0.8272189349112427 [0.827219,0.827219]
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
0.7999881649801763 [0.79845,0.801527]
f_measure
0.8036108354685348 [0.796813,0.810409]
f_measure
0.7997037037037037 [0.792,0.807407]
f_measure
0.7614114025220532 [0.755906,0.766917]
f_measure
0.7922954020947984 [0.790698,0.793893]
f_measure
0.7423038802349148 [0.743295,0.741313]
f_measure
0.7192266157783399 [0.720307,0.718147]
f_measure
0.6880877975088494 [0.698885,0.677291]
f_measure
0.7687381404174574 [0.779412,0.758065]
f_measure
0.7846153846153847 [0.784615,0.784615]
kappa
0.6000000000000001
kappa
0.6076923076923078
kappa
0.6000000000000001
kappa
0.523076923076923
kappa
0.5846153846153845
kappa
0.48461538461538467
kappa
0.43846153846153846
kappa
0.3769230769230769
kappa
0.5384615384615385
kappa
0.5692307692307692
kb_relative_information_score
159.27219741707177
kb_relative_information_score
157.14739835291886
kb_relative_information_score
152.28463330105382
kb_relative_information_score
140.16254935308262
kb_relative_information_score
151.80738904963266
kb_relative_information_score
125.57522566603137
kb_relative_information_score
118.37230599214485
kb_relative_information_score
97.62383739041901
kb_relative_information_score
139.00498897091882
kb_relative_information_score
149.19756724135152
mean_absolute_error
0.19394340702033006
mean_absolute_error
0.1974974215076025
mean_absolute_error
0.20933024805762362
mean_absolute_error
0.22997160079739265
mean_absolute_error
0.20993603210514977
mean_absolute_error
0.25823942774169023
mean_absolute_error
0.27212351311333205
mean_absolute_error
0.3115726411597451
mean_absolute_error
0.2332012111819805
mean_absolute_error
0.2131842463092464
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
0.8000710227272727 [0.804688,0.795455]
precision
0.8053094714311196 [0.826446,0.784173]
precision
0.8017857142857143 [0.825,0.778571]
precision
0.7620967741935483 [0.774194,0.75]
precision
0.792376893939394 [0.796875,0.787879]
precision
0.7423220308894017 [0.740458,0.744186]
precision
0.7192437422332681 [0.717557,0.72093]
precision
0.6893691658243654 [0.676259,0.702479]
precision
0.771544521365481 [0.746479,0.79661]
precision
0.7846153846153846 [0.784615,0.784615]
predictive_accuracy
0.8
predictive_accuracy
0.8038461538461539
predictive_accuracy
0.8
predictive_accuracy
0.7615384615384616
predictive_accuracy
0.7923076923076923
predictive_accuracy
0.7423076923076922
predictive_accuracy
0.7192307692307692
predictive_accuracy
0.6884615384615383
predictive_accuracy
0.7692307692307692
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
0.8 [0.792308,0.807692]
recall
0.8038461538461539 [0.769231,0.838462]
recall
0.8 [0.761538,0.838462]
recall
0.7615384615384615 [0.738462,0.784615]
recall
0.7923076923076923 [0.784615,0.8]
recall
0.7423076923076923 [0.746154,0.738462]
recall
0.7192307692307692 [0.723077,0.715385]
recall
0.6884615384615385 [0.723077,0.653846]
recall
0.7692307692307693 [0.815385,0.723077]
recall
0.7846153846153846 [0.784615,0.784615]
relative_absolute_error
0.3878868140406601
relative_absolute_error
0.394994843015205
relative_absolute_error
0.41866049611524725
relative_absolute_error
0.45994320159478536
relative_absolute_error
0.41987206421029954
relative_absolute_error
0.5164788554833805
relative_absolute_error
0.5442470262266641
relative_absolute_error
0.6231452823194902
relative_absolute_error
0.46640242236396096
relative_absolute_error
0.4263684926184928
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
0.4164968275594177
root_mean_squared_error
0.41473938889401424
root_mean_squared_error
0.42472045742305203
root_mean_squared_error
0.44689509062004773
root_mean_squared_error
0.4191731014522228
root_mean_squared_error
0.48120230115063983
root_mean_squared_error
0.48583449991560324
root_mean_squared_error
0.5299008835278113
root_mean_squared_error
0.44668719088134146
root_mean_squared_error
0.4266193594443799
root_relative_squared_error
0.8329936551188354
root_relative_squared_error
0.8294787777880285
root_relative_squared_error
0.8494409148461041
root_relative_squared_error
0.8937901812400955
root_relative_squared_error
0.8383462029044456
root_relative_squared_error
0.9624046023012797
root_relative_squared_error
0.9716689998312065
root_relative_squared_error
1.0598017670556226
root_relative_squared_error
0.8933743817626829
root_relative_squared_error
0.8532387188887598
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
2054.5261860024766
usercpu_time_millis
1898.3143600016774
usercpu_time_millis
1944.3174209955032
usercpu_time_millis
1876.3234429970908
usercpu_time_millis
1926.0301900030754
usercpu_time_millis
1923.3763400006865
usercpu_time_millis
1936.8241890006175
usercpu_time_millis
2202.118465997046
usercpu_time_millis
1931.2683770040167
usercpu_time_millis
1931.1093499964045
usercpu_time_millis_testing
4.624463999789441
usercpu_time_millis_testing
4.588882999087218
usercpu_time_millis_testing
4.479248997085961
usercpu_time_millis_testing
4.590607997670304
usercpu_time_millis_testing
4.614796001987997
usercpu_time_millis_testing
4.460915999516146
usercpu_time_millis_testing
4.573222999169957
usercpu_time_millis_testing
4.589704996760702
usercpu_time_millis_testing
4.481792002479779
usercpu_time_millis_testing
5.314107998856343
usercpu_time_millis_training
2049.901722002687
usercpu_time_millis_training
1893.7254770025902
usercpu_time_millis_training
1939.8381719984172
usercpu_time_millis_training
1871.7328349994204
usercpu_time_millis_training
1921.4153940010874
usercpu_time_millis_training
1918.9154240011703
usercpu_time_millis_training
1932.2509660014475
usercpu_time_millis_training
2197.528761000285
usercpu_time_millis_training
1926.7865850015369
usercpu_time_millis_training
1925.7952419975481