Run
2012969

Run 2012969

Task 23 (Supervised Classification) cmc Uploaded 07-04-2017 by Jeroen van Hoof
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  • Fri_Apr__7_03.49.19_2017 NumPy_1.12.0. Python_3.6.0. run_task SciPy_0.19.0. sklearn.pipeline.Pipeline Sklearn_0.18.1.
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Flow

sklearn.pipeline.Pipeline(gradientboostingclassifier=sklearn.ensemble.gradi ent_boosting.GradientBoostingClassifier)(1)Automatically created scikit-learn flow.
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(3)_criterionfriedman_mse
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(3)_initNone
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(3)_learning_rate0.184368248985
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(3)_lossdeviance
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(3)_max_depth1
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_estimators256
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(3)_presortauto
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(3)_random_state3
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(3)_subsample1.0
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(3)_verbose0
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(3)_warm_startFalse
sklearn.pipeline.Pipeline(gradientboostingclassifier=sklearn.ensemble.gradient_boosting.GradientBoostingClassifier)(1)_steps[('gradientboostingclassifier', GradientBoostingClassifier(criterion='friedman_mse', init=None, learning_rate=0.18436824898475251, loss='deviance', max_depth=1, 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=256, presort='auto', random_state=3, 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
0.7369
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.5573
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.3141
Cross-validation details (10-fold Crossvalidation)
KB relative information score
355.2819
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.3567
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.4308
Cross-validation details (10-fold Crossvalidation)
Number of instances
1473
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.5586
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.5608
Cross-validation details (10-fold Crossvalidation)
Prior entropy
1.5392
Cross-validation details (10-fold Crossvalidation)
Recall
0.5608
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.8281
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.4641
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.4253
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.9163
Cross-validation details (10-fold Crossvalidation)