Run
1850779

Run 1850779

Task 145677 (Supervised Classification) Bioresponse Uploaded 10-03-2017 by János Szedelényi
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  • Fri_Mar_10_22.29.43_2017 NumPy_1.12.0. Python_3.5.2. run_task SciPy_0.18.1. sklearn.ensemble.voting_classifier.VotingClassifier Sklearn_0.18.1.
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Flow

sklearn.ensemble.voting_classifier.VotingClassifier(estimators=sklearn.ense mble.forest.RandomForestClassifier,voting=xgboost.sklearn.XGBClassifier,wei ghts=sklearn.ensemble.forest.ExtraTreesClassifier)(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_state55
sklearn.ensemble.forest.RandomForestClassifier(16)_verbose0
sklearn.ensemble.forest.RandomForestClassifier(16)_warm_startFalse
xgboost.sklearn.XGBClassifier(3)_base_score0.5
xgboost.sklearn.XGBClassifier(3)_colsample_bylevel1
xgboost.sklearn.XGBClassifier(3)_colsample_bytree1
xgboost.sklearn.XGBClassifier(3)_gamma0
xgboost.sklearn.XGBClassifier(3)_learning_rate0.1
xgboost.sklearn.XGBClassifier(3)_max_delta_step0
xgboost.sklearn.XGBClassifier(3)_max_depth3
xgboost.sklearn.XGBClassifier(3)_min_child_weight1
xgboost.sklearn.XGBClassifier(3)_missingNone
xgboost.sklearn.XGBClassifier(3)_n_estimators100
xgboost.sklearn.XGBClassifier(3)_nthread-1
xgboost.sklearn.XGBClassifier(3)_objectivebinary:logistic
xgboost.sklearn.XGBClassifier(3)_reg_alpha0
xgboost.sklearn.XGBClassifier(3)_reg_lambda1
xgboost.sklearn.XGBClassifier(3)_scale_pos_weight1
xgboost.sklearn.XGBClassifier(3)_seed0
xgboost.sklearn.XGBClassifier(3)_silentTrue
xgboost.sklearn.XGBClassifier(3)_subsample1
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_state55
sklearn.ensemble.forest.ExtraTreesClassifier(5)_verbose0
sklearn.ensemble.forest.ExtraTreesClassifier(5)_warm_startFalse
sklearn.ensemble.voting_classifier.VotingClassifier(estimators=sklearn.ensemble.forest.RandomForestClassifier,voting=xgboost.sklearn.XGBClassifier,weights=sklearn.ensemble.forest.ExtraTreesClassifier)(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=55, verbose=0, warm_start=False)
sklearn.ensemble.voting_classifier.VotingClassifier(estimators=sklearn.ensemble.forest.RandomForestClassifier,voting=xgboost.sklearn.XGBClassifier,weights=sklearn.ensemble.forest.ExtraTreesClassifier)(1)_n_jobs-1
sklearn.ensemble.voting_classifier.VotingClassifier(estimators=sklearn.ensemble.forest.RandomForestClassifier,voting=xgboost.sklearn.XGBClassifier,weights=sklearn.ensemble.forest.ExtraTreesClassifier)(1)_votingXGBClassifier(base_score=0.5, colsample_bylevel=1, colsample_bytree=1, gamma=0, learning_rate=0.1, max_delta_step=0, max_depth=3, min_child_weight=1, missing=None, n_estimators=100, nthread=-1, objective='binary:logistic', reg_alpha=0, reg_lambda=1, scale_pos_weight=1, seed=0, silent=True, subsample=1)
sklearn.ensemble.voting_classifier.VotingClassifier(estimators=sklearn.ensemble.forest.RandomForestClassifier,voting=xgboost.sklearn.XGBClassifier,weights=sklearn.ensemble.forest.ExtraTreesClassifier)(1)_weightsExtraTreesClassifier(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=55, 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
0.882
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.8082
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.6132
Cross-validation details (10-fold Crossvalidation)
KB relative information score
1603.6241
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.3024
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
0.8084
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.8086
Cross-validation details (10-fold Crossvalidation)
Prior entropy
0.9948
Cross-validation details (10-fold Crossvalidation)
Recall
0.8086
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.6092
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.4982
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.3735
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.7497
Cross-validation details (10-fold Crossvalidation)