Run
10434997

Run 10434997

Task 9952 (Supervised Classification) phoneme Uploaded 24-12-2019 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"5"
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_state27049

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.

18 Evaluation measures

Area under ROC curve
0.7302 ± 0.0357
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.5971
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.0201 ± 0.0552
Cross-validation details (10-fold Crossvalidation)
KB relative information score
0.0708 ± 0.02
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.3821 ± 0.0096
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.4147 ± 0.0003
Cross-validation details (10-fold Crossvalidation)
Weighted recall
0.7076 ± 0.0035
Cross-validation details (10-fold Crossvalidation)
Number of instances
5404
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.6618
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.7076 ± 0.0035
Cross-validation details (10-fold Crossvalidation)
Prior entropy
0.8732 ± 0.001
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.9214 ± 0.0234
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.4554 ± 0.0004
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.4372 ± 0.0044
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.9602 ± 0.0097
Cross-validation details (10-fold Crossvalidation)
Unweighted recall
0.5072 ± 0.0228
Cross-validation details (10-fold Crossvalidation)