9954189
6892
Scikit-learn Bot
3512
Supervised Classification
8890
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)(3)
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n_jobs
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memory
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axis
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verbose
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true
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with_std
true
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memory
null
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copy
true
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fill_value
-1
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missing_values
NaN
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strategy
"constant"
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verbose
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categorical_features
null
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categories
null
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dtype
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handle_unknown
"ignore"
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n_values
null
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sparse
true
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threshold
0.0
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criterion
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init
null
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learning_rate
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loss
"deviance"
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max_depth
5
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max_features
0.018202510492690505
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max_leaf_nodes
null
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min_impurity_decrease
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min_impurity_split
null
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min_samples_leaf
14
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min_samples_split
14
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min_weight_fraction_leaf
0.23020296837219067
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n_estimators
409
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n_iter_no_change
12
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presort
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random_state
15380
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subsample
0.8461555582424501
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tol
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validation_fraction
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verbose
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warm_start
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8899
openml-python
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synthetic_control
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-1
20828893
description
https://api.openml.org/data/download/20828893/description.xml
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20828894
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average_cost
0
kappa
0
kb_relative_information_score
5.937003610707775
mean_absolute_error
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mean_prior_absolute_error
0.2777777777777742
number_of_instances
600 [100,100,100,100,100,100]
predictive_accuracy
0.16666666666666669
prior_entropy
2.584962500721156
recall
0.16666666666666666 [0,0,0,0,1,0]
relative_absolute_error
1.0000000000000115
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0.37267799624996256
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0.37284858467953574
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1.0004577367896408
total_cost
0
area_under_roc_curve
0.5 [0.5,0.5,0.5,0.5,0.5,0.5]
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0.5 [0.5,0.5,0.5,0.5,0.5,0.5]
area_under_roc_curve
0.5 [0.5,0.5,0.5,0.5,0.5,0.5]
area_under_roc_curve
0.5 [0.5,0.5,0.5,0.5,0.5,0.5]
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0.5 [0.5,0.5,0.5,0.5,0.5,0.5]
area_under_roc_curve
0.5 [0.5,0.5,0.5,0.5,0.5,0.5]
area_under_roc_curve
0.5 [0.5,0.5,0.5,0.5,0.5,0.5]
area_under_roc_curve
0.5 [0.5,0.5,0.5,0.5,0.5,0.5]
area_under_roc_curve
0.5 [0.5,0.5,0.5,0.5,0.5,0.5]
area_under_roc_curve
0.5 [0.5,0.5,0.5,0.5,0.5,0.5]
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mean_absolute_error
0.27777777777777785
mean_absolute_error
0.27777777777777785
mean_absolute_error
0.27777777777777785
mean_absolute_error
0.27777777777777785
mean_absolute_error
0.27777777777777785
mean_prior_absolute_error
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mean_prior_absolute_error
0.2777777777777782
mean_prior_absolute_error
0.2777777777777782
mean_prior_absolute_error
0.2777777777777782
mean_prior_absolute_error
0.2777777777777782
mean_prior_absolute_error
0.2777777777777782
mean_prior_absolute_error
0.2777777777777782
mean_prior_absolute_error
0.2777777777777782
mean_prior_absolute_error
0.2777777777777782
mean_prior_absolute_error
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number_of_instances
60 [10,10,10,10,10,10]
number_of_instances
60 [10,10,10,10,10,10]
number_of_instances
60 [10,10,10,10,10,10]
number_of_instances
60 [10,10,10,10,10,10]
number_of_instances
60 [10,10,10,10,10,10]
number_of_instances
60 [10,10,10,10,10,10]
number_of_instances
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number_of_instances
60 [10,10,10,10,10,10]
number_of_instances
60 [10,10,10,10,10,10]
number_of_instances
60 [10,10,10,10,10,10]
predictive_accuracy
0.16666666666666669
predictive_accuracy
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predictive_accuracy
0.16666666666666669
predictive_accuracy
0.16666666666666669
predictive_accuracy
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predictive_accuracy
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predictive_accuracy
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predictive_accuracy
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predictive_accuracy
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predictive_accuracy
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prior_entropy
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prior_entropy
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prior_entropy
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prior_entropy
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recall
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recall
0.16666666666666666 [0,0,0,0,1,0]
recall
0.16666666666666666 [0,0,0,0,1,0]
recall
0.16666666666666666 [0,0,0,0,1,0]
recall
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recall
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recall
0.16666666666666666 [0,0,0,0,1,0]
recall
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recall
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recall
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relative_absolute_error
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usercpu_time_millis_testing
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usercpu_time_millis_testing
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usercpu_time_millis_testing
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usercpu_time_millis_training
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usercpu_time_millis_training
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usercpu_time_millis_training
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usercpu_time_millis_training
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