Run
1852799

Run 1852799

Task 145677 (Supervised Classification) Bioresponse Uploaded 16-03-2017 by Thomas Hagebols
0 likes downloaded by 0 people 0 issues 0 downvotes , 0 total downloads
  • NumPy_1.11.3. Python_3.5.2. run_task SciPy_0.18.1. sklearn.ensemble.gradient_boosting.GradientBoostingClassifier Sklearn_0.18.1. Thu_Mar_16_16.29.18_2017
Issue #Downvotes for this reason By


Flow

sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(3)Automatically created sub-component.
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(3)_criterionfriedman_mse
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(3)_initNone
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(3)_learning_rate0.2
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(3)_lossdeviance
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(3)_max_depth9
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(3)_max_featuresNone
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(3)_max_leaf_nodesNone
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(3)_min_impurity_split1e-07
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(3)_min_samples_leaf1
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(3)_min_samples_split2
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(3)_min_weight_fraction_leaf0.0
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(3)_n_estimators50
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(3)_presortauto
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(3)_random_state0
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(3)_subsample1.0
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(3)_verbose0
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(3)_warm_startFalse

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
0.8717
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.7984
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.5933
Cross-validation details (10-fold Crossvalidation)
KB relative information score
2044.6716
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.2318
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.4964
Cross-validation details (10-fold Crossvalidation)
Number of instances
3751
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.7985
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.7987
Cross-validation details (10-fold Crossvalidation)
Prior entropy
0.9948
Cross-validation details (10-fold Crossvalidation)
Recall
0.7987
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.4669
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.4982
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.3936
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.7901
Cross-validation details (10-fold Crossvalidation)
Total cost