OpenML
5951758

Run 5951758

Task 3512 (Supervised Classification) synthetic_control Uploaded 14-07-2017 by Jan van Rijn
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  • openml-pimp openml-python Sklearn_0.18.1. study_71
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Flow

sklearn.pipeline.Pipeline(imputation=openmlstudy14.preprocessing.Conditiona lImputer,hotencoding=sklearn.preprocessing.data.OneHotEncoder,variencethres hold=sklearn.feature_selection.variance_threshold.VarianceThreshold,classif ier=sklearn.ensemble.weight_boosting.AdaBoostClassifier(base_estimator=skle arn.tree.tree.DecisionTreeClassifier))(1)Automatically created scikit-learn flow.
sklearn.tree.tree.DecisionTreeClassifier(10)_class_weightnull
sklearn.tree.tree.DecisionTreeClassifier(10)_criterion"gini"
sklearn.tree.tree.DecisionTreeClassifier(10)_max_depth5
sklearn.tree.tree.DecisionTreeClassifier(10)_max_featuresnull
sklearn.tree.tree.DecisionTreeClassifier(10)_max_leaf_nodesnull
sklearn.tree.tree.DecisionTreeClassifier(10)_min_impurity_split1e-07
sklearn.tree.tree.DecisionTreeClassifier(10)_min_samples_leaf1
sklearn.tree.tree.DecisionTreeClassifier(10)_min_samples_split2
sklearn.tree.tree.DecisionTreeClassifier(10)_min_weight_fraction_leaf0.0
sklearn.tree.tree.DecisionTreeClassifier(10)_presortfalse
sklearn.tree.tree.DecisionTreeClassifier(10)_random_state41487
sklearn.tree.tree.DecisionTreeClassifier(10)_splitter"best"
openmlstudy14.preprocessing.ConditionalImputer(2)_axis0
openmlstudy14.preprocessing.ConditionalImputer(2)_categorical_features[]
openmlstudy14.preprocessing.ConditionalImputer(2)_copytrue
openmlstudy14.preprocessing.ConditionalImputer(2)_fill_empty0
openmlstudy14.preprocessing.ConditionalImputer(2)_missing_values"NaN"
openmlstudy14.preprocessing.ConditionalImputer(2)_strategy"median"
openmlstudy14.preprocessing.ConditionalImputer(2)_strategy_nominal"most_frequent"
openmlstudy14.preprocessing.ConditionalImputer(2)_verbose0
sklearn.preprocessing.data.OneHotEncoder(7)_categorical_features[]
sklearn.preprocessing.data.OneHotEncoder(7)_dtype{"oml-python:serialized_object": "type", "value": "np.float64"}
sklearn.preprocessing.data.OneHotEncoder(7)_handle_unknown"ignore"
sklearn.preprocessing.data.OneHotEncoder(7)_n_values"auto"
sklearn.preprocessing.data.OneHotEncoder(7)_sparsefalse
sklearn.feature_selection.variance_threshold.VarianceThreshold(4)_threshold0.0
sklearn.ensemble.weight_boosting.AdaBoostClassifier(base_estimator=sklearn.tree.tree.DecisionTreeClassifier)(2)_algorithm"SAMME"
sklearn.ensemble.weight_boosting.AdaBoostClassifier(base_estimator=sklearn.tree.tree.DecisionTreeClassifier)(2)_learning_rate0.8933139542489222
sklearn.ensemble.weight_boosting.AdaBoostClassifier(base_estimator=sklearn.tree.tree.DecisionTreeClassifier)(2)_n_estimators77
sklearn.ensemble.weight_boosting.AdaBoostClassifier(base_estimator=sklearn.tree.tree.DecisionTreeClassifier)(2)_random_state40336

Result files

xml
Description

XML file describing the run, including user-defined evaluation measures.

arff
Predictions

ARFF file with instance-level predictions generated by the model.

17 Evaluation measures

Area under ROC curve
0.9993 ± 0.0015
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.9817 ± 0.0184
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.978 ± 0.022
Cross-validation details (10-fold Crossvalidation)
KB relative information score
40.0591 ± 0.1072
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.2707 ± 0.0002
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.2778
Cross-validation details (10-fold Crossvalidation)
Number of instances
600
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.9819 ± 0.0161
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.9817 ± 0.0183
Cross-validation details (10-fold Crossvalidation)
Prior entropy
2.585
Cross-validation details (10-fold Crossvalidation)
Recall
0.9817 ± 0.0183
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.9745 ± 0.0007
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.3727
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.3632 ± 0.0003
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.9746 ± 0.0007
Cross-validation details (10-fold Crossvalidation)