10222637
1
Jan van Rijn
3543
Supervised Classification
9666
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,gradientboostingclassifier=sklearn.ensemble.gradient_boosting.GradientBoostingClassifier)(4)
8148069
copy
true
9559
fill_value
-1
9559
missing_values
NaN
9559
strategy
"constant"
9559
verbose
0
9559
n_jobs
null
9606
remainder
"passthrough"
9606
sparse_threshold
0.3
9606
transformer_weights
null
9606
transformers
[{"oml-python:serialized_object": "component_reference", "value": {"key": "numeric", "step_name": "numeric", "argument_1": [1, 3]}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "nominal", "step_name": "nominal", "argument_1": [0, 2, 4]}}]
9606
memory
null
9607
steps
[{"oml-python:serialized_object": "component_reference", "value": {"key": "imputer", "step_name": "imputer"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "standardscaler", "step_name": "standardscaler"}}]
9607
axis
0
9608
copy
true
9608
missing_values
"NaN"
9608
strategy
"median"
9608
verbose
0
9608
copy
true
9609
with_mean
true
9609
with_std
true
9609
memory
null
9610
steps
[{"oml-python:serialized_object": "component_reference", "value": {"key": "simpleimputer", "step_name": "simpleimputer"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "onehotencoder", "step_name": "onehotencoder"}}]
9610
categorical_features
null
9611
categories
null
9611
dtype
{"oml-python:serialized_object": "type", "value": "np.float64"}
9611
handle_unknown
"ignore"
9611
n_values
null
9611
sparse
true
9611
threshold
0.0
9612
memory
null
9666
steps
[{"oml-python:serialized_object": "component_reference", "value": {"key": "columntransformer", "step_name": "columntransformer"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "variancethreshold", "step_name": "variancethreshold"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "gradientboostingclassifier", "step_name": "gradientboostingclassifier"}}]
9666
criterion
"friedman_mse"
9667
init
null
9667
learning_rate
3.3058496822474024e-05
9667
loss
"deviance"
9667
max_depth
5
9667
max_features
0.3712520122396866
9667
max_leaf_nodes
null
9667
min_impurity_decrease
0.7505509550421775
9667
min_impurity_split
null
9667
min_samples_leaf
7
9667
min_samples_split
3
9667
min_weight_fraction_leaf
0.10833943903836213
9667
n_estimators
1468
9667
n_iter_no_change
621
9667
presort
"auto"
9667
random_state
55299
9667
subsample
0.3235366701796184
9667
tol
0.0008439498139005972
9667
validation_fraction
0.4693489849493405
9667
verbose
0
9667
warm_start
false
9667
openml-python
Sklearn_0.20.3.
451
irish
https://www.openml.org/data/download/52563/irish.arff
-1
21366190
description
https://api.openml.org/data/download/21366190/description.xml
-1
21366191
predictions
https://api.openml.org/data/download/21366191/predictions.arff
area_under_roc_curve
0.9971482273640547 [0.997148,0.997148]
average_cost
0
kappa
0
kb_relative_information_score
20.239704163663145
mean_absolute_error
0.47815904978109863
mean_prior_absolute_error
0.49375298804780854
number_of_instances
500 [278,222]
predictive_accuracy
0.556
prior_entropy
0.9910046621528215
recall
0.556 [1,0]
relative_absolute_error
0.9684175313482862
root_mean_prior_squared_error
0.49685415342632255
root_mean_squared_error
0.4833061803902836
root_relative_squared_error
0.9727324951545404
total_cost
0
area_under_roc_curve
1 [1,1]
area_under_roc_curve
0.9935064935064934 [0.993506,0.993506]
area_under_roc_curve
0.9983766233766234 [0.998377,0.998377]
area_under_roc_curve
0.991883116883117 [0.991883,0.991883]
area_under_roc_curve
1 [1,1]
area_under_roc_curve
1 [1,1]
area_under_roc_curve
1 [1,1]
area_under_roc_curve
1 [1,1]
area_under_roc_curve
0.998389694041868 [0.99839,0.99839]
area_under_roc_curve
0.9903381642512078 [0.990338,0.990338]
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
kappa
0
kappa
0
kappa
0
kappa
0
kappa
0
kappa
0
kappa
0
kappa
0
kappa
0
kappa
0
kb_relative_information_score
2.2514757164416555
kb_relative_information_score
1.844675114054745
kb_relative_information_score
2.008242355803002
kb_relative_information_score
1.750142093524635
kb_relative_information_score
2.1020860760432494
kb_relative_information_score
2.0151912152218245
kb_relative_information_score
2.0133225286269796
kb_relative_information_score
2.220570576054223
kb_relative_information_score
2.143021085638008
kb_relative_information_score
1.8909774022548347
mean_absolute_error
0.47618219816102064
mean_absolute_error
0.4791296159772231
mean_absolute_error
0.47783982302392564
mean_absolute_error
0.47974145340266555
mean_absolute_error
0.47722735365332936
mean_absolute_error
0.4777512563295359
mean_absolute_error
0.47780797705823347
mean_absolute_error
0.47633664197258996
mean_absolute_error
0.4788259055010991
mean_absolute_error
0.4807482727313628
mean_prior_absolute_error
0.49330677290836705
mean_prior_absolute_error
0.49330677290836705
mean_prior_absolute_error
0.49330677290836705
mean_prior_absolute_error
0.49330677290836705
mean_prior_absolute_error
0.49330677290836705
mean_prior_absolute_error
0.49330677290836705
mean_prior_absolute_error
0.49330677290836705
mean_prior_absolute_error
0.49330677290836705
mean_prior_absolute_error
0.49553784860557826
mean_prior_absolute_error
0.49553784860557826
number_of_instances
50 [28,22]
number_of_instances
50 [28,22]
number_of_instances
50 [28,22]
number_of_instances
50 [28,22]
number_of_instances
50 [28,22]
number_of_instances
50 [28,22]
number_of_instances
50 [28,22]
number_of_instances
50 [28,22]
number_of_instances
50 [27,23]
number_of_instances
50 [27,23]
predictive_accuracy
0.56
predictive_accuracy
0.56
predictive_accuracy
0.56
predictive_accuracy
0.56
predictive_accuracy
0.56
predictive_accuracy
0.56
predictive_accuracy
0.56
predictive_accuracy
0.56
predictive_accuracy
0.54
predictive_accuracy
0.54
prior_entropy
0.9910046621528215
prior_entropy
0.9910046621528215
prior_entropy
0.9910046621528215
prior_entropy
0.9910046621528215
prior_entropy
0.9910046621528215
prior_entropy
0.9910046621528215
prior_entropy
0.9910046621528215
prior_entropy
0.9910046621528215
prior_entropy
0.9910046621528215
prior_entropy
0.9910046621528215
recall
0.56 [1,0]
recall
0.56 [1,0]
recall
0.56 [1,0]
recall
0.56 [1,0]
recall
0.56 [1,0]
recall
0.56 [1,0]
recall
0.56 [1,0]
recall
0.56 [1,0]
recall
0.54 [1,0]
recall
0.54 [1,0]
relative_absolute_error
0.9652861552125347
relative_absolute_error
0.9712609724623071
relative_absolute_error
0.968646386520798
relative_absolute_error
0.9725012502347675
relative_absolute_error
0.9674048277094617
relative_absolute_error
0.9684668497715505
relative_absolute_error
0.9685818304120213
relative_absolute_error
0.9655992338484893
relative_absolute_error
0.966275142955264
relative_absolute_error
0.9701544979544293
root_mean_prior_squared_error
0.49640490996518694
root_mean_prior_squared_error
0.49640490996518694
root_mean_prior_squared_error
0.49640490996518694
root_mean_prior_squared_error
0.49640490996518694
root_mean_prior_squared_error
0.49640490996518694
root_mean_prior_squared_error
0.49640490996518694
root_mean_prior_squared_error
0.49640490996518694
root_mean_prior_squared_error
0.49640490996518694
root_mean_prior_squared_error
0.49864707994207336
root_mean_prior_squared_error
0.49864707994207336
root_mean_squared_error
0.480983568423162
root_mean_squared_error
0.48433735495360947
root_mean_squared_error
0.48290928220574575
root_mean_squared_error
0.48495225003772974
root_mean_squared_error
0.48209136358475446
root_mean_squared_error
0.4828758304706202
root_mean_squared_error
0.48293266016011016
root_mean_squared_error
0.4812561964540522
root_mean_squared_error
0.48434491575621086
root_mean_squared_error
0.4863518120573405
root_relative_squared_error
0.9689339463964882
root_relative_squared_error
0.9756900973996737
root_relative_squared_error
0.9728132669751643
root_relative_squared_error
0.9769287940196635
root_relative_squared_error
0.9711655825857237
root_relative_squared_error
0.9727458789730433
root_relative_squared_error
0.9728603615020215
root_relative_squared_error
0.9694831513407128
root_relative_squared_error
0.9713180628922485
root_relative_squared_error
0.975342745642547
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
1135.3066279989434
usercpu_time_millis
1027.5725840037921
usercpu_time_millis
1024.621800002933
usercpu_time_millis
1026.0046550029074
usercpu_time_millis
1029.6523430006346
usercpu_time_millis
1021.5859370000544
usercpu_time_millis
1029.2838020031922
usercpu_time_millis
1034.6964250020392
usercpu_time_millis
1032.8493019987945
usercpu_time_millis
1024.6263620028913
usercpu_time_millis_testing
5.179110001336085
usercpu_time_millis_testing
5.064598000899423
usercpu_time_millis_testing
5.220508002821589
usercpu_time_millis_testing
5.4390430013882
usercpu_time_millis_testing
5.49347900232533
usercpu_time_millis_testing
5.068902999482816
usercpu_time_millis_testing
5.1150550025340635
usercpu_time_millis_testing
5.958936002571136
usercpu_time_millis_testing
5.089186000986956
usercpu_time_millis_testing
5.311779001203831
usercpu_time_millis_training
1130.1275179976074
usercpu_time_millis_training
1022.5079860028927
usercpu_time_millis_training
1019.4012920001114
usercpu_time_millis_training
1020.5656120015192
usercpu_time_millis_training
1024.1588639983092
usercpu_time_millis_training
1016.5170340005716
usercpu_time_millis_training
1024.1687470006582
usercpu_time_millis_training
1028.737488999468
usercpu_time_millis_training
1027.7601159978076
usercpu_time_millis_training
1019.3145830016874