Run
1863677

Run 1863677

Task 3889 (Supervised Classification) sylva_agnostic Uploaded 28-03-2017 by Randal Olson
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  • NumPy_1.11.3. Python_3.6.0. run_task SciPy_0.19.0. sklearn.pipeline.Pipeline Sklearn_0.18.1. Tue_Mar_28_02.39.43_2017
Issue #Downvotes for this reason By


Flow

sklearn.pipeline.Pipeline(imputer=sklearn.preprocessing.imputation.Imputer, pca=sklearn.decomposition.pca.PCA,gradientboostingclassifier=sklearn.ensemb le.gradient_boosting.GradientBoostingClassifier)(1)Automatically created scikit-learn flow.
sklearn.preprocessing.imputation.Imputer(3)_axis0
sklearn.preprocessing.imputation.Imputer(3)_copyTrue
sklearn.preprocessing.imputation.Imputer(3)_missing_valuesNaN
sklearn.preprocessing.imputation.Imputer(3)_strategymedian
sklearn.preprocessing.imputation.Imputer(3)_verbose0
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_estimators500
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(3)_presortauto
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(3)_random_stateNone
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(3)_subsample1.0
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(3)_verbose0
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(3)_warm_startFalse
sklearn.decomposition.pca.PCA(1)_copyTrue
sklearn.decomposition.pca.PCA(1)_iterated_powerauto
sklearn.decomposition.pca.PCA(1)_n_componentsNone
sklearn.decomposition.pca.PCA(1)_random_stateNone
sklearn.decomposition.pca.PCA(1)_svd_solverauto
sklearn.decomposition.pca.PCA(1)_tol0.0
sklearn.decomposition.pca.PCA(1)_whitenFalse
sklearn.pipeline.Pipeline(imputer=sklearn.preprocessing.imputation.Imputer,pca=sklearn.decomposition.pca.PCA,gradientboostingclassifier=sklearn.ensemble.gradient_boosting.GradientBoostingClassifier)(1)_steps[('imputer', Imputer(axis=0, copy=True, missing_values='NaN', strategy='median', verbose=0)), ('pca', PCA(copy=True, iterated_power='auto', n_components=None, random_state=None, svd_solver='auto', tol=0.0, whiten=False)), ('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=500, presort='auto', random_state=None, 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
0.9972
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.99
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.9127
Cross-validation details (10-fold Crossvalidation)
KB relative information score
12237.1047
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.0132
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.1156
Cross-validation details (10-fold Crossvalidation)
Number of instances
14395
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.9899
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.9901
Cross-validation details (10-fold Crossvalidation)
Prior entropy
0.3338
Cross-validation details (10-fold Crossvalidation)
Recall
0.9901
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.114
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.2403
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.0883
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.3674
Cross-validation details (10-fold Crossvalidation)