Run
2083558

Run 2083558

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_19.30.33_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_depth1
sklearn.tree.tree.ExtraTreeClassifier(1)_max_features0.45
sklearn.tree.tree.ExtraTreeClassifier(1)_max_leaf_nodesNone
sklearn.tree.tree.ExtraTreeClassifier(1)_min_impurity_split1e-07
sklearn.tree.tree.ExtraTreeClassifier(1)_min_samples_leaf14
sklearn.tree.tree.ExtraTreeClassifier(1)_min_samples_split19
sklearn.tree.tree.ExtraTreeClassifier(1)_min_weight_fraction_leaf0.0
sklearn.tree.tree.ExtraTreeClassifier(1)_random_state3
sklearn.tree.tree.ExtraTreeClassifier(1)_splitterrandom
sklearn.ensemble.weight_boosting.AdaBoostClassifier(base_estimator=sklearn.tree.tree.ExtraTreeClassifier)(1)_algorithmSAMME
sklearn.ensemble.weight_boosting.AdaBoostClassifier(base_estimator=sklearn.tree.tree.ExtraTreeClassifier)(1)_base_estimatorExtraTreeClassifier(class_weight=None, criterion='gini', max_depth=1, max_features=0.45, max_leaf_nodes=None, min_impurity_split=1e-07, min_samples_leaf=14, min_samples_split=19, min_weight_fraction_leaf=0.0, random_state=3, 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_estimators70
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
0.6676
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.4354
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.1628
Cross-validation details (10-fold Crossvalidation)
KB relative information score
0.9351
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.4438
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
0.4907
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.4437
Cross-validation details (10-fold Crossvalidation)
Prior entropy
1.5845
Cross-validation details (10-fold Crossvalidation)
Recall
0.4437
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.9988
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.4713
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.4707
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.9987
Cross-validation details (10-fold Crossvalidation)