Run
2088112

Run 2088112

Task 9960 (Supervised Classification) wall-robot-navigation Uploaded 27-04-2017 by Jeroen van Hoof
0 likes downloaded by 0 people 0 issues 0 downvotes , 0 total downloads
  • NumPy_1.12.0. Python_3.6.0. run_task SciPy_0.19.0. sklearn.ensemble.gradient_boosting.GradientBoostingClassifier Sklearn_0.18.1. Thu_Apr_27_23.34.41_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_rate1
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(3)_lossdeviance
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(3)_max_depth1
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_estimators512
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(3)_presortauto
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(3)_random_state3
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
0.9999
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.998
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.997
Cross-validation details (10-fold Crossvalidation)
KB relative information score
5431.1935
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.0013
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.3312
Cross-validation details (10-fold Crossvalidation)
Number of instances
5456
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.998
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.998
Cross-validation details (10-fold Crossvalidation)
Prior entropy
1.7151
Cross-validation details (10-fold Crossvalidation)
Recall
0.998
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.0039
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.4069
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.0317
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.078
Cross-validation details (10-fold Crossvalidation)