10220504
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)
8145936
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
"most_frequent"
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
"mae"
9667
init
null
9667
learning_rate
0.00021320720265849375
9667
loss
"deviance"
9667
max_depth
24
9667
max_features
0.4923618367076916
9667
max_leaf_nodes
null
9667
min_impurity_decrease
0.2403327170864803
9667
min_impurity_split
null
9667
min_samples_leaf
17
9667
min_samples_split
11
9667
min_weight_fraction_leaf
0.45447729897511463
9667
n_estimators
722
9667
n_iter_no_change
85
9667
presort
"auto"
9667
random_state
43747
9667
subsample
0.14327859206196314
9667
tol
3.359711996228305e-05
9667
validation_fraction
0.49612817069727555
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
21361924
description
https://api.openml.org/data/download/21361924/description.xml
-1
21361925
predictions
https://api.openml.org/data/download/21361925/predictions.arff
area_under_roc_curve
0.5 [0.5,0.5]
average_cost
0
kappa
0
kb_relative_information_score
2.1986841465863223
mean_absolute_error
0.492051362326885
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
0.9965536902821563
root_mean_prior_squared_error
0.49685415342632255
root_mean_squared_error
0.49707957137461684
root_relative_squared_error
1.0004536903772259
total_cost
0
area_under_roc_curve
0.5 [0.5,0.5]
area_under_roc_curve
0.5 [0.5,0.5]
area_under_roc_curve
0.5 [0.5,0.5]
area_under_roc_curve
0.5 [0.5,0.5]
area_under_roc_curve
0.5 [0.5,0.5]
area_under_roc_curve
0.5 [0.5,0.5]
area_under_roc_curve
0.5 [0.5,0.5]
area_under_roc_curve
0.5 [0.5,0.5]
area_under_roc_curve
0.5 [0.5,0.5]
area_under_roc_curve
0.5 [0.5,0.5]
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
0.23557330141996252
kb_relative_information_score
0.23557330141996252
kb_relative_information_score
0.23557330141996252
kb_relative_information_score
0.23557330141996252
kb_relative_information_score
0.23557330141996252
kb_relative_information_score
0.23557330141996252
kb_relative_information_score
0.23557330141996252
kb_relative_information_score
0.23557330141996252
kb_relative_information_score
0.15704886761330827
kb_relative_information_score
0.15704886761330827
mean_absolute_error
0.4914836024930907
mean_absolute_error
0.4914836024930907
mean_absolute_error
0.4914836024930907
mean_absolute_error
0.4914836024930907
mean_absolute_error
0.4914836024930907
mean_absolute_error
0.4914836024930907
mean_absolute_error
0.4914836024930907
mean_absolute_error
0.4914836024930907
mean_absolute_error
0.4943224016620605
mean_absolute_error
0.4943224016620605
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
0.9963041853155035
relative_absolute_error
0.9963041853155035
relative_absolute_error
0.9963041853155035
relative_absolute_error
0.9963041853155035
relative_absolute_error
0.9963041853155035
relative_absolute_error
0.9963041853155035
relative_absolute_error
0.9963041853155035
relative_absolute_error
0.9963041853155035
relative_absolute_error
0.9975472167324091
relative_absolute_error
0.9975472167324091
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
0.4965081474096677
root_mean_squared_error
0.4965081474096677
root_mean_squared_error
0.4965081474096677
root_mean_squared_error
0.4965081474096677
root_mean_squared_error
0.4965081474096677
root_mean_squared_error
0.4965081474096677
root_mean_squared_error
0.4965081474096677
root_mean_squared_error
0.4965081474096677
root_mean_squared_error
0.4993587283838644
root_mean_squared_error
0.4993587283838644
root_relative_squared_error
1.0002079702323816
root_relative_squared_error
1.0002079702323816
root_relative_squared_error
1.0002079702323816
root_relative_squared_error
1.0002079702323816
root_relative_squared_error
1.0002079702323816
root_relative_squared_error
1.0002079702323816
root_relative_squared_error
1.0002079702323816
root_relative_squared_error
1.0002079702323816
root_relative_squared_error
1.0014271585464287
root_relative_squared_error
1.0014271585464287
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
74.25828800114687
usercpu_time_millis
67.49856300302781
usercpu_time_millis
66.97595099831233
usercpu_time_millis
66.90681700274581
usercpu_time_millis
67.94973899741308
usercpu_time_millis
67.62125699970056
usercpu_time_millis
66.96634699983406
usercpu_time_millis
62.99470100202598
usercpu_time_millis
62.365608999243705
usercpu_time_millis
62.78512700009742
usercpu_time_millis_testing
3.1922410016704816
usercpu_time_millis_testing
3.103350001765648
usercpu_time_millis_testing
2.9235209985927213
usercpu_time_millis_testing
2.9186370011302643
usercpu_time_millis_testing
3.1795129980309866
usercpu_time_millis_testing
2.9355549995671026
usercpu_time_millis_testing
2.9297170003701467
usercpu_time_millis_testing
2.7031120007450227
usercpu_time_millis_testing
2.9817030008416623
usercpu_time_millis_testing
2.962262002256466
usercpu_time_millis_training
71.06604699947638
usercpu_time_millis_training
64.39521300126216
usercpu_time_millis_training
64.0524299997196
usercpu_time_millis_training
63.98818000161555
usercpu_time_millis_training
64.77022599938209
usercpu_time_millis_training
64.68570200013346
usercpu_time_millis_training
64.03662999946391
usercpu_time_millis_training
60.291589001280954
usercpu_time_millis_training
59.38390599840204
usercpu_time_millis_training
59.82286499784095