Run
2016496

Run 2016496

Task 31 (Supervised Classification) credit-g Uploaded 08-04-2017 by Jeroen van Hoof
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  • NumPy_1.12.0. Python_3.6.0. run_task Sat_Apr__8_04.07.28_2017 SciPy_0.19.0. sklearn.pipeline.Pipeline Sklearn_0.18.1.
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Flow

sklearn.pipeline.Pipeline(dualimputer=helper.dual_imputer.DualImputer,rando mforestclassifier=sklearn.ensemble.forest.RandomForestClassifier)(1)Automatically created scikit-learn flow.
sklearn.ensemble.forest.RandomForestClassifier(16)_bootstrapTrue
sklearn.ensemble.forest.RandomForestClassifier(16)_class_weightNone
sklearn.ensemble.forest.RandomForestClassifier(16)_criteriongini
sklearn.ensemble.forest.RandomForestClassifier(16)_max_depthNone
sklearn.ensemble.forest.RandomForestClassifier(16)_max_featuressqrt
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_split16
sklearn.ensemble.forest.RandomForestClassifier(16)_min_weight_fraction_leaf0.0
sklearn.ensemble.forest.RandomForestClassifier(16)_n_estimators256
sklearn.ensemble.forest.RandomForestClassifier(16)_n_jobs-1
sklearn.ensemble.forest.RandomForestClassifier(16)_oob_scoreFalse
sklearn.ensemble.forest.RandomForestClassifier(16)_random_state3
sklearn.ensemble.forest.RandomForestClassifier(16)_verbose0
sklearn.ensemble.forest.RandomForestClassifier(16)_warm_startFalse
sklearn.pipeline.Pipeline(dualimputer=helper.dual_imputer.DualImputer,randomforestclassifier=sklearn.ensemble.forest.RandomForestClassifier)(1)_steps[('DualImputer', ), ('randomforestclassifier', RandomForestClassifier(bootstrap=True, class_weight=None, criterion='gini', max_depth=None, max_features='sqrt', max_leaf_nodes=None, min_impurity_split=1e-07, min_samples_leaf=1, min_samples_split=16, min_weight_fraction_leaf=0.0, n_estimators=256, n_jobs=-1, oob_score=False, random_state=3, 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
0.7995
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.7515
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.3838
Cross-validation details (10-fold Crossvalidation)
KB relative information score
187.1133
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.342
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.4202
Cross-validation details (10-fold Crossvalidation)
Number of instances
1000
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.7637
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.773
Cross-validation details (10-fold Crossvalidation)
Prior entropy
0.8818
Cross-validation details (10-fold Crossvalidation)
Recall
0.773
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.814
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.4583
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.402
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.8772
Cross-validation details (10-fold Crossvalidation)