Run
1924168

Run 1924168

Task 37 (Supervised Classification) diabetes Uploaded 02-04-2017 by Jeroen van Hoof
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  • NumPy_1.12.1. Python_3.5.3. run_task SciPy_0.18.1. sklearn.pipeline.Pipeline Sklearn_0.18.1. Sun_Apr__2_01.25.04_2017
Issue #Downvotes for this reason By


Flow

sklearn.pipeline.Pipeline(dualimputer=helper.dual_imputer.DualImputer,extra treesclassifier=sklearn.ensemble.forest.ExtraTreesClassifier)(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_depth10
sklearn.ensemble.forest.ExtraTreesClassifier(5)_max_features1.0
sklearn.ensemble.forest.ExtraTreesClassifier(5)_max_leaf_nodesNone
sklearn.ensemble.forest.ExtraTreesClassifier(5)_min_impurity_split1e-07
sklearn.ensemble.forest.ExtraTreesClassifier(5)_min_samples_leaf2
sklearn.ensemble.forest.ExtraTreesClassifier(5)_min_samples_split24
sklearn.ensemble.forest.ExtraTreesClassifier(5)_min_weight_fraction_leaf0.0
sklearn.ensemble.forest.ExtraTreesClassifier(5)_n_estimators1024
sklearn.ensemble.forest.ExtraTreesClassifier(5)_n_jobs-1
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.pipeline.Pipeline(dualimputer=helper.dual_imputer.DualImputer,extratreesclassifier=sklearn.ensemble.forest.ExtraTreesClassifier)(1)_steps[('dualimputer', ), ('extratreesclassifier', ExtraTreesClassifier(bootstrap=False, class_weight=None, criterion='gini', max_depth=10, max_features=1.0, max_leaf_nodes=None, min_impurity_split=1e-07, min_samples_leaf=2, min_samples_split=24, min_weight_fraction_leaf=0.0, n_estimators=1024, n_jobs=-1, oob_score=False, random_state=None, 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
0.84
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.7671
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.4776
Cross-validation details (10-fold Crossvalidation)
KB relative information score
242.788
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.3183
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.4545
Cross-validation details (10-fold Crossvalidation)
Number of instances
768
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.7697
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.7747
Cross-validation details (10-fold Crossvalidation)
Prior entropy
0.9335
Cross-validation details (10-fold Crossvalidation)
Recall
0.7747
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.7002
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.4766
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.3921
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.8226
Cross-validation details (10-fold Crossvalidation)