Run
1849165

Run 1849165

Task 145677 (Supervised Classification) Bioresponse Uploaded 09-03-2017 by János Szedelényi
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  • NumPy_1.12.0. Python_3.5.2. run_task SciPy_0.18.1. sklearn.ensemble.voting_classifier.VotingClassifier Sklearn_0.18.1. Thu_Mar__9_14.26.31_2017
Issue #Downvotes for this reason By


Flow

sklearn.ensemble.voting_classifier.VotingClassifier(estimators=sklearn.ense mble.forest.RandomForestClassifier,voting=sklearn.ensemble.forest.ExtraTree sClassifier,weights=sklearn.ensemble.gradient_boosting.GradientBoostingClas sifier)(1)Automatically created scikit-learn flow.
sklearn.ensemble.forest.RandomForestClassifier(16)_bootstrapTrue
sklearn.ensemble.forest.RandomForestClassifier(16)_class_weightNone
sklearn.ensemble.forest.RandomForestClassifier(16)_criterionentropy
sklearn.ensemble.forest.RandomForestClassifier(16)_max_depthNone
sklearn.ensemble.forest.RandomForestClassifier(16)_max_features0.1
sklearn.ensemble.forest.RandomForestClassifier(16)_max_leaf_nodesNone
sklearn.ensemble.forest.RandomForestClassifier(16)_min_impurity_split1e-07
sklearn.ensemble.forest.RandomForestClassifier(16)_min_samples_leaf1
sklearn.ensemble.forest.RandomForestClassifier(16)_min_samples_split2
sklearn.ensemble.forest.RandomForestClassifier(16)_min_weight_fraction_leaf0.0
sklearn.ensemble.forest.RandomForestClassifier(16)_n_estimators100
sklearn.ensemble.forest.RandomForestClassifier(16)_n_jobs-1
sklearn.ensemble.forest.RandomForestClassifier(16)_oob_scoreFalse
sklearn.ensemble.forest.RandomForestClassifier(16)_random_state123
sklearn.ensemble.forest.RandomForestClassifier(16)_verbose0
sklearn.ensemble.forest.RandomForestClassifier(16)_warm_startFalse
sklearn.ensemble.forest.ExtraTreesClassifier(5)_bootstrapFalse
sklearn.ensemble.forest.ExtraTreesClassifier(5)_class_weightNone
sklearn.ensemble.forest.ExtraTreesClassifier(5)_criteriongini
sklearn.ensemble.forest.ExtraTreesClassifier(5)_max_depthNone
sklearn.ensemble.forest.ExtraTreesClassifier(5)_max_featuresauto
sklearn.ensemble.forest.ExtraTreesClassifier(5)_max_leaf_nodesNone
sklearn.ensemble.forest.ExtraTreesClassifier(5)_min_impurity_split1e-07
sklearn.ensemble.forest.ExtraTreesClassifier(5)_min_samples_leaf1
sklearn.ensemble.forest.ExtraTreesClassifier(5)_min_samples_split2
sklearn.ensemble.forest.ExtraTreesClassifier(5)_min_weight_fraction_leaf0.0
sklearn.ensemble.forest.ExtraTreesClassifier(5)_n_estimators100
sklearn.ensemble.forest.ExtraTreesClassifier(5)_n_jobs-1
sklearn.ensemble.forest.ExtraTreesClassifier(5)_oob_scoreFalse
sklearn.ensemble.forest.ExtraTreesClassifier(5)_random_state444
sklearn.ensemble.forest.ExtraTreesClassifier(5)_verbose0
sklearn.ensemble.forest.ExtraTreesClassifier(5)_warm_startFalse
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(3)_criterionfriedman_mse
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(3)_initNone
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(3)_learning_rate0.05
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(3)_lossdeviance
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(3)_max_depth6
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(3)_max_featuresNone
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(3)_max_leaf_nodesNone
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(3)_min_impurity_split1e-07
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(3)_min_samples_leaf1
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(3)_min_samples_split2
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(3)_min_weight_fraction_leaf0.0
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(3)_n_estimators100
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(3)_presortauto
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(3)_random_state555
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(3)_subsample0.5
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(3)_verbose0
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(3)_warm_startFalse
sklearn.ensemble.voting_classifier.VotingClassifier(estimators=sklearn.ensemble.forest.RandomForestClassifier,voting=sklearn.ensemble.forest.ExtraTreesClassifier,weights=sklearn.ensemble.gradient_boosting.GradientBoostingClassifier)(1)_estimatorsRandomForestClassifier(bootstrap=True, class_weight=None, criterion='entropy', max_depth=None, max_features=0.1, max_leaf_nodes=None, min_impurity_split=1e-07, min_samples_leaf=1, min_samples_split=2, min_weight_fraction_leaf=0.0, n_estimators=100, n_jobs=-1, oob_score=False, random_state=123, verbose=0, warm_start=False)
sklearn.ensemble.voting_classifier.VotingClassifier(estimators=sklearn.ensemble.forest.RandomForestClassifier,voting=sklearn.ensemble.forest.ExtraTreesClassifier,weights=sklearn.ensemble.gradient_boosting.GradientBoostingClassifier)(1)_n_jobs-1
sklearn.ensemble.voting_classifier.VotingClassifier(estimators=sklearn.ensemble.forest.RandomForestClassifier,voting=sklearn.ensemble.forest.ExtraTreesClassifier,weights=sklearn.ensemble.gradient_boosting.GradientBoostingClassifier)(1)_votingExtraTreesClassifier(bootstrap=False, class_weight=None, criterion='gini', max_depth=None, max_features='auto', max_leaf_nodes=None, min_impurity_split=1e-07, min_samples_leaf=1, min_samples_split=2, min_weight_fraction_leaf=0.0, n_estimators=100, n_jobs=-1, oob_score=False, random_state=444, verbose=0, warm_start=False)
sklearn.ensemble.voting_classifier.VotingClassifier(estimators=sklearn.ensemble.forest.RandomForestClassifier,voting=sklearn.ensemble.forest.ExtraTreesClassifier,weights=sklearn.ensemble.gradient_boosting.GradientBoostingClassifier)(1)_weightsGradientBoostingClassifier(criterion='friedman_mse', init=None, learning_rate=0.05, loss='deviance', max_depth=6, max_features=None, max_leaf_nodes=None, min_impurity_split=1e-07, min_samples_leaf=1, min_samples_split=2, min_weight_fraction_leaf=0.0, n_estimators=100, presort='auto', random_state=555, subsample=0.5, verbose=0, warm_start=False)

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
0.8818
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.8084
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.6135
Cross-validation details (10-fold Crossvalidation)
KB relative information score
1647.8148
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.2958
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.4964
Cross-validation details (10-fold Crossvalidation)
Number of instances
3751
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.8088
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.8089
Cross-validation details (10-fold Crossvalidation)
Prior entropy
0.9948
Cross-validation details (10-fold Crossvalidation)
Recall
0.8089
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.5959
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.4982
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.3725
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.7476
Cross-validation details (10-fold Crossvalidation)