Run
10560306

Run 10560306

Task 10101 (Supervised Classification) blood-transfusion-service-center Uploaded 13-08-2021 by Sergey Redyuk
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Flow

sklearn.ensemble.voting_classifier.VotingClassifier(DecisionTreeClassifier= sklearn.tree.tree.DecisionTreeClassifier,ExtraTreeClassifier=sklearn.tree.t ree.ExtraTreeClassifier)(2)Soft Voting/Majority Rule classifier for unfitted estimators. .. versionadded:: 0.17
sklearn.tree.tree.DecisionTreeClassifier(66)_class_weightnull
sklearn.tree.tree.DecisionTreeClassifier(66)_criterion"gini"
sklearn.tree.tree.DecisionTreeClassifier(66)_max_depthnull
sklearn.tree.tree.DecisionTreeClassifier(66)_max_featuresnull
sklearn.tree.tree.DecisionTreeClassifier(66)_max_leaf_nodesnull
sklearn.tree.tree.DecisionTreeClassifier(66)_min_impurity_split1e-07
sklearn.tree.tree.DecisionTreeClassifier(66)_min_samples_leaf1
sklearn.tree.tree.DecisionTreeClassifier(66)_min_samples_split2
sklearn.tree.tree.DecisionTreeClassifier(66)_min_weight_fraction_leaf0.0
sklearn.tree.tree.DecisionTreeClassifier(66)_presortfalse
sklearn.tree.tree.DecisionTreeClassifier(66)_random_state33330
sklearn.tree.tree.DecisionTreeClassifier(66)_splitter"best"
sklearn.tree.tree.ExtraTreeClassifier(28)_class_weightnull
sklearn.tree.tree.ExtraTreeClassifier(28)_criterion"gini"
sklearn.tree.tree.ExtraTreeClassifier(28)_max_depth1000
sklearn.tree.tree.ExtraTreeClassifier(28)_max_features"auto"
sklearn.tree.tree.ExtraTreeClassifier(28)_max_leaf_nodesnull
sklearn.tree.tree.ExtraTreeClassifier(28)_min_impurity_split1e-07
sklearn.tree.tree.ExtraTreeClassifier(28)_min_samples_leaf1
sklearn.tree.tree.ExtraTreeClassifier(28)_min_samples_split2
sklearn.tree.tree.ExtraTreeClassifier(28)_min_weight_fraction_leaf0.0
sklearn.tree.tree.ExtraTreeClassifier(28)_random_state61221
sklearn.tree.tree.ExtraTreeClassifier(28)_splitter"random"
sklearn.ensemble.voting_classifier.VotingClassifier(DecisionTreeClassifier=sklearn.tree.tree.DecisionTreeClassifier,ExtraTreeClassifier=sklearn.tree.tree.ExtraTreeClassifier)(2)_estimators[{"oml-python:serialized_object": "component_reference", "value": {"key": "DecisionTreeClassifier", "step_name": "DecisionTreeClassifier"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "ExtraTreeClassifier", "step_name": "ExtraTreeClassifier"}}]
sklearn.ensemble.voting_classifier.VotingClassifier(DecisionTreeClassifier=sklearn.tree.tree.DecisionTreeClassifier,ExtraTreeClassifier=sklearn.tree.tree.ExtraTreeClassifier)(2)_n_jobs1
sklearn.ensemble.voting_classifier.VotingClassifier(DecisionTreeClassifier=sklearn.tree.tree.DecisionTreeClassifier,ExtraTreeClassifier=sklearn.tree.tree.ExtraTreeClassifier)(2)_voting"hard"
sklearn.ensemble.voting_classifier.VotingClassifier(DecisionTreeClassifier=sklearn.tree.tree.DecisionTreeClassifier,ExtraTreeClassifier=sklearn.tree.tree.ExtraTreeClassifier)(2)_weightsnull

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.

18 Evaluation measures

Area under ROC curve
0.5522 ± 0.0541
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.7016 ± 0.0444
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.124 ± 0.1283
Cross-validation details (10-fold Crossvalidation)
KB relative information score
0.169 ± 0.137
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.2674 ± 0.0438
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.363 ± 0.0023
Cross-validation details (10-fold Crossvalidation)
Weighted recall
0.7326 ± 0.0438
Cross-validation details (10-fold Crossvalidation)
Number of instances
748
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.689 ± 0.0539
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.7326 ± 0.0438
Cross-validation details (10-fold Crossvalidation)
Prior entropy
0.7916 ± 0.0072
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.7365 ± 0.1211
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.4258 ± 0.0027
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.5171 ± 0.0422
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
1.2143 ± 0.0999
Cross-validation details (10-fold Crossvalidation)
Unweighted recall
0.5522 ± 0.0541
Cross-validation details (10-fold Crossvalidation)