OpenML
555322

Run 555322

Task 14951 (Supervised Classification) eeg-eye-state Uploaded 13-04-2016 by Pattarawat Chormai
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  • NumPy_1.10.0.post2. Python_2.7.9. run_task SciPy_0.17.0. sklearn.ensemble.gradient_boosting.GradientBoostingClassifier Sklearn_0.17.1. Wed_Apr_13_23.47.42_2016
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Flow

sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(2)Flow generated by run_task
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(2)_presortauto
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(2)_lossdeviance
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(2)_verbose0
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(2)_subsample1.0
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(2)_max_leaf_nodesNone
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(2)_learning_rate0.0001
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(2)_warm_startFalse
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(2)_min_samples_leaf1
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(2)_n_estimators90
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(2)_min_samples_split2
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(2)_initNone
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(2)_min_weight_fraction_leaf0.0
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(2)_random_state0
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(2)_max_featuresNone
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(2)_max_depth1

Result files

Description

XML file describing the run, including user-defined evaluation measures.

Predictions

ARFF file with instance-level predictions generated by the model.

17 Evaluation measures

Area under ROC curve
0.5496
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.3917
Per class
Cross-validation details (10-fold Crossvalidation)
KB relative information score
6.1886
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.4946
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.4948
Cross-validation details (10-fold Crossvalidation)
Number of instances
14980
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.3038
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.5512
Cross-validation details (10-fold Crossvalidation)
Prior entropy
0.9924
Cross-validation details (10-fold Crossvalidation)
Recall
0.5512
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.9997
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.4974
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.4972
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.9997
Cross-validation details (10-fold Crossvalidation)