10098532
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)
8023685
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
7
8783
min_weight_fraction_leaf
0.0
8783
presort
false
8783
random_state
10005
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
21117601
description
https://api.openml.org/data/download/21117601/description.xml
-1
21117602
predictions
https://api.openml.org/data/download/21117602/predictions.arff
area_under_roc_curve
0.8224020710059171 [0.822402,0.822402]
average_cost
0
f_measure
0.7510503994929253 [0.756125,0.745976]
kappa
0.5023076923076923
kb_relative_information_score
1271.587073385655
mean_absolute_error
0.2576328889016128
mean_prior_absolute_error
0.5
number_of_instances
2600 [1300,1300]
precision
0.7515719915528236 [0.741316,0.761828]
predictive_accuracy
0.7511538461538462
prior_entropy
1
recall
0.7511538461538462 [0.771538,0.730769]
relative_absolute_error
0.5152657778032256
root_mean_prior_squared_error
0.5
root_mean_squared_error
0.434280499007305
root_relative_squared_error
0.86856099801461
total_cost
0
area_under_roc_curve
0.8550591715976331 [0.855059,0.855059]
area_under_roc_curve
0.7892011834319527 [0.789201,0.789201]
area_under_roc_curve
0.8209763313609467 [0.820976,0.820976]
area_under_roc_curve
0.8356508875739646 [0.835651,0.835651]
area_under_roc_curve
0.8210355029585799 [0.821036,0.821036]
area_under_roc_curve
0.824792899408284 [0.824793,0.824793]
area_under_roc_curve
0.8601479289940829 [0.860148,0.860148]
area_under_roc_curve
0.7437869822485207 [0.743787,0.743787]
area_under_roc_curve
0.8197337278106509 [0.819734,0.819734]
area_under_roc_curve
0.8511834319526628 [0.851183,0.851183]
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
0.7768702651515151 [0.780303,0.773438]
f_measure
0.7384460618971538 [0.740458,0.736434]
f_measure
0.7691761363636365 [0.772727,0.765625]
f_measure
0.74609375 [0.742187,0.75]
f_measure
0.7692307692307693 [0.769231,0.769231]
f_measure
0.738322183411284 [0.744361,0.732283]
f_measure
0.7999881649801763 [0.79845,0.801527]
f_measure
0.675367144301088 [0.697842,0.652893]
f_measure
0.7598188211454795 [0.780142,0.739496]
f_measure
0.7345800476394785 [0.737643,0.731518]
kappa
0.5538461538461539
kappa
0.476923076923077
kappa
0.5384615384615385
kappa
0.49230769230769234
kappa
0.5384615384615385
kappa
0.476923076923077
kappa
0.6000000000000001
kappa
0.3538461538461539
kappa
0.523076923076923
kappa
0.46923076923076934
kb_relative_information_score
143.3226529552088
kb_relative_information_score
115.19496027148662
kb_relative_information_score
130.22382788284608
kb_relative_information_score
131.79528854702
kb_relative_information_score
130.2875757350833
kb_relative_information_score
125.73025490852466
kb_relative_information_score
143.93127806139276
kb_relative_information_score
88.71022118670803
kb_relative_information_score
126.47143629890802
kb_relative_information_score
135.91957753847547
mean_absolute_error
0.22490791602454457
mean_absolute_error
0.2813253628604398
mean_absolute_error
0.25498039974540077
mean_absolute_error
0.2477293686432483
mean_absolute_error
0.2535847841468617
mean_absolute_error
0.25864521118923034
mean_absolute_error
0.22705600948316357
mean_absolute_error
0.33049562527652543
mean_absolute_error
0.25955481100360844
mean_absolute_error
0.2380494006431043
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
0.777185501066098 [0.768657,0.785714]
precision
0.7385179924242424 [0.734848,0.742188]
precision
0.769485903814262 [0.761194,0.777778]
precision
0.7463871120587537 [0.753968,0.738806]
precision
0.7692307692307693 [0.769231,0.769231]
precision
0.738970588235294 [0.727941,0.75]
precision
0.8000710227272727 [0.804688,0.795455]
precision
0.6803812741312741 [0.655405,0.705357]
precision
0.7692495126705653 [0.723684,0.814815]
precision
0.7347403942928187 [0.729323,0.740157]
predictive_accuracy
0.7769230769230769
predictive_accuracy
0.7384615384615384
predictive_accuracy
0.7692307692307692
predictive_accuracy
0.7461538461538462
predictive_accuracy
0.7692307692307692
predictive_accuracy
0.7384615384615384
predictive_accuracy
0.8
predictive_accuracy
0.676923076923077
predictive_accuracy
0.7615384615384616
predictive_accuracy
0.7346153846153847
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
0.7769230769230769 [0.792308,0.761538]
recall
0.7384615384615385 [0.746154,0.730769]
recall
0.7692307692307693 [0.784615,0.753846]
recall
0.7461538461538462 [0.730769,0.761538]
recall
0.7692307692307693 [0.769231,0.769231]
recall
0.7384615384615385 [0.761538,0.715385]
recall
0.8 [0.792308,0.807692]
recall
0.676923076923077 [0.746154,0.607692]
recall
0.7615384615384615 [0.846154,0.676923]
recall
0.7346153846153847 [0.746154,0.723077]
relative_absolute_error
0.44981583204908915
relative_absolute_error
0.5626507257208796
relative_absolute_error
0.5099607994908015
relative_absolute_error
0.4954587372864966
relative_absolute_error
0.5071695682937234
relative_absolute_error
0.5172904223784607
relative_absolute_error
0.45411201896632714
relative_absolute_error
0.6609912505530509
relative_absolute_error
0.5191096220072169
relative_absolute_error
0.4760988012862086
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
0.40954653057889107
root_mean_squared_error
0.4553525209811452
root_mean_squared_error
0.42888663886420225
root_mean_squared_error
0.42282649091813435
root_mean_squared_error
0.4328856193625356
root_mean_squared_error
0.43933097105307256
root_mean_squared_error
0.3974340635317087
root_mean_squared_error
0.5009572323007552
root_mean_squared_error
0.4316059817617544
root_mean_squared_error
0.4154490103120486
root_relative_squared_error
0.819093061157782
root_relative_squared_error
0.9107050419622904
root_relative_squared_error
0.8577732777284045
root_relative_squared_error
0.8456529818362687
root_relative_squared_error
0.8657712387250711
root_relative_squared_error
0.8786619421061451
root_relative_squared_error
0.7948681270634174
root_relative_squared_error
1.0019144646015103
root_relative_squared_error
0.8632119635235088
root_relative_squared_error
0.8308980206240971
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
2026.251620001858
usercpu_time_millis
1918.299670000124
usercpu_time_millis
1920.9222580029746
usercpu_time_millis
1879.6195240029192
usercpu_time_millis
1908.8779850026185
usercpu_time_millis
1922.8603099982138
usercpu_time_millis
1933.2737420008925
usercpu_time_millis
1958.344083999691
usercpu_time_millis
1914.9881029989047
usercpu_time_millis
1891.8792659969768
usercpu_time_millis_testing
5.201433999900473
usercpu_time_millis_testing
5.0856630005000625
usercpu_time_millis_testing
5.410214002040448
usercpu_time_millis_testing
5.013589001464425
usercpu_time_millis_testing
4.96432300133165
usercpu_time_millis_testing
5.042863998824032
usercpu_time_millis_testing
5.001995999919018
usercpu_time_millis_testing
5.167896000784822
usercpu_time_millis_testing
4.937573998176958
usercpu_time_millis_testing
5.034316000092076
usercpu_time_millis_training
2021.0501860019576
usercpu_time_millis_training
1913.214006999624
usercpu_time_millis_training
1915.512044000934
usercpu_time_millis_training
1874.6059350014548
usercpu_time_millis_training
1903.9136620012869
usercpu_time_millis_training
1917.8174459993897
usercpu_time_millis_training
1928.2717460009735
usercpu_time_millis_training
1953.1761879989062
usercpu_time_millis_training
1910.0505290007277
usercpu_time_millis_training
1886.8449499968847