Run
2083560

Run 2083560

Task 47 (Supervised Classification) tae Uploaded 23-04-2017 by Jeroen van Hoof
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  • NumPy_1.12.1. Python_3.5.3. run_task SciPy_0.19.0. sklearn.ensemble.weight_boosting.AdaBoostClassifier Sklearn_0.18.1. Sun_Apr_23_19.43.37_2017
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Flow

sklearn.ensemble.weight_boosting.AdaBoostClassifier(base_estimator=sklearn. tree.tree.ExtraTreeClassifier)(1)Automatically created scikit-learn flow.
sklearn.tree.tree.ExtraTreeClassifier(1)_class_weightNone
sklearn.tree.tree.ExtraTreeClassifier(1)_criteriongini
sklearn.tree.tree.ExtraTreeClassifier(1)_max_depthNone
sklearn.tree.tree.ExtraTreeClassifier(1)_max_featuresauto
sklearn.tree.tree.ExtraTreeClassifier(1)_max_leaf_nodesNone
sklearn.tree.tree.ExtraTreeClassifier(1)_min_impurity_split1e-07
sklearn.tree.tree.ExtraTreeClassifier(1)_min_samples_leaf1
sklearn.tree.tree.ExtraTreeClassifier(1)_min_samples_split2
sklearn.tree.tree.ExtraTreeClassifier(1)_min_weight_fraction_leaf0.0
sklearn.tree.tree.ExtraTreeClassifier(1)_random_stateNone
sklearn.tree.tree.ExtraTreeClassifier(1)_splitterrandom
sklearn.ensemble.weight_boosting.AdaBoostClassifier(base_estimator=sklearn.tree.tree.ExtraTreeClassifier)(1)_algorithmSAMME.R
sklearn.ensemble.weight_boosting.AdaBoostClassifier(base_estimator=sklearn.tree.tree.ExtraTreeClassifier)(1)_base_estimatorExtraTreeClassifier(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, random_state=None, splitter='random')
sklearn.ensemble.weight_boosting.AdaBoostClassifier(base_estimator=sklearn.tree.tree.ExtraTreeClassifier)(1)_learning_rate1
sklearn.ensemble.weight_boosting.AdaBoostClassifier(base_estimator=sklearn.tree.tree.ExtraTreeClassifier)(1)_n_estimators10
sklearn.ensemble.weight_boosting.AdaBoostClassifier(base_estimator=sklearn.tree.tree.ExtraTreeClassifier)(1)_random_state3

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
0.8417
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.6882
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.533
Cross-validation details (10-fold Crossvalidation)
KB relative information score
86.7098
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.2085
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.4443
Cross-validation details (10-fold Crossvalidation)
Number of instances
151
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.6879
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.6887
Cross-validation details (10-fold Crossvalidation)
Prior entropy
1.5845
Cross-validation details (10-fold Crossvalidation)
Recall
0.6887
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.4693
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.4713
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.436
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.925
Cross-validation details (10-fold Crossvalidation)