Run
10434863

Run 10434863

Task 3917 (Supervised Classification) kc1 Uploaded 23-12-2019 by Peng YU
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Flow

sklearn.ensemble._weight_boosting.AdaBoostClassifier(base_estimator=bsplitz .DecisionStumpClassifierV3)(1)An AdaBoost classifier. An AdaBoost [1] classifier is a meta-estimator that begins by fitting a classifier on the original dataset and then fits additional copies of the classifier on the same dataset but where the weights of incorrectly classified instances are adjusted such that subsequent classifiers focus more on difficult cases. This class implements the algorithm known as AdaBoost-SAMME [2].
bsplitz.DecisionStumpClassifierV3(1)_default_feature_type"numerical"
bsplitz.DecisionStumpClassifierV3(1)_nominal_method"bsplitz"
bsplitz.DecisionStumpClassifierV3(1)_non_default_feature_colmns"21"
sklearn.ensemble._weight_boosting.AdaBoostClassifier(base_estimator=bsplitz.DecisionStumpClassifierV3)(1)_algorithm"SAMME.R"
sklearn.ensemble._weight_boosting.AdaBoostClassifier(base_estimator=bsplitz.DecisionStumpClassifierV3)(1)_learning_rate1.0
sklearn.ensemble._weight_boosting.AdaBoostClassifier(base_estimator=bsplitz.DecisionStumpClassifierV3)(1)_n_estimators50
sklearn.ensemble._weight_boosting.AdaBoostClassifier(base_estimator=bsplitz.DecisionStumpClassifierV3)(1)_random_state9067

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.

16 Evaluation measures

Area under ROC curve
0.7608 ± 0.031
Per class
Cross-validation details (10-fold Crossvalidation)
KB relative information score
-0.0072 ± 0.0364
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.2353 ± 0.0037
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.2616 ± 0.0016
Cross-validation details (10-fold Crossvalidation)
Weighted recall
0.8454 ± 0.0024
Cross-validation details (10-fold Crossvalidation)
Number of instances
2109
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.8454 ± 0.0024
Cross-validation details (10-fold Crossvalidation)
Prior entropy
0.6212 ± 0.0058
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.8994 ± 0.0141
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.3615 ± 0.0023
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.3424 ± 0.0037
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.9473 ± 0.0111
Cross-validation details (10-fold Crossvalidation)
Unweighted recall
0.5
Cross-validation details (10-fold Crossvalidation)