Run
1852530

Run 1852530

Task 145677 (Supervised Classification) Bioresponse Uploaded 14-03-2017 by Stanley Clark
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  • NumPy_1.12.0. Python_3.5.2. run_task SciPy_0.18.1. sklearn.pipeline.Pipeline Sklearn_0.18.1. Tue_Mar_14_12.40.29_2017
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Flow

sklearn.pipeline.Pipeline(standardscaler=sklearn.preprocessing.data.Standar dScaler,selectfrommodel=sklearn.feature_selection.from_model.SelectFromMode l(estimator=sklearn.ensemble.forest.ExtraTreesClassifier),gradientboostingc lassifier=sklearn.ensemble.gradient_boosting.GradientBoostingClassifier)(1)Automatically created scikit-learn flow.
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_estimators10
sklearn.ensemble.forest.ExtraTreesClassifier(5)_n_jobs1
sklearn.ensemble.forest.ExtraTreesClassifier(5)_oob_scoreFalse
sklearn.ensemble.forest.ExtraTreesClassifier(5)_random_stateNone
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_rate0.1
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(3)_lossdeviance
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(3)_max_depth3
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_estimators1000
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(3)_presortauto
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(3)_random_state0
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(3)_subsample1.0
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(3)_verbose0
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(3)_warm_startFalse
sklearn.preprocessing.data.StandardScaler(1)_copyTrue
sklearn.preprocessing.data.StandardScaler(1)_with_meanTrue
sklearn.preprocessing.data.StandardScaler(1)_with_stdTrue
sklearn.feature_selection.from_model.SelectFromModel(estimator=sklearn.ensemble.forest.ExtraTreesClassifier)(1)_estimatorExtraTreesClassifier(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=10, n_jobs=1, oob_score=False, random_state=None, verbose=0, warm_start=False)
sklearn.feature_selection.from_model.SelectFromModel(estimator=sklearn.ensemble.forest.ExtraTreesClassifier)(1)_prefitFalse
sklearn.feature_selection.from_model.SelectFromModel(estimator=sklearn.ensemble.forest.ExtraTreesClassifier)(1)_thresholdNone
sklearn.pipeline.Pipeline(standardscaler=sklearn.preprocessing.data.StandardScaler,selectfrommodel=sklearn.feature_selection.from_model.SelectFromModel(estimator=sklearn.ensemble.forest.ExtraTreesClassifier),gradientboostingclassifier=sklearn.ensemble.gradient_boosting.GradientBoostingClassifier)(1)_steps[('standardscaler', StandardScaler(copy=True, with_mean=True, with_std=True)), ('selectfrommodel', SelectFromModel(estimator=ExtraTreesClassifier(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=10, n_jobs=1, oob_score=False, random_state=None, verbose=0, warm_start=False), prefit=False, threshold=None)), ('gradientboostingclassifier', GradientBoostingClassifier(criterion='friedman_mse', init=None, learning_rate=0.1, loss='deviance', max_depth=3, 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=1000, presort='auto', random_state=0, subsample=1.0, 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
0.8672
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.7948
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.5861
Cross-validation details (10-fold Crossvalidation)
KB relative information score
1943.266
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.2472
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
0.795
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.7953
Cross-validation details (10-fold Crossvalidation)
Prior entropy
0.9948
Cross-validation details (10-fold Crossvalidation)
Recall
0.7953
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.4979
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.4982
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.3895
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.7818
Cross-validation details (10-fold Crossvalidation)