Issue | #Downvotes for this reason | By |
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sklearn.ensemble._weight_boosting.AdaBoostClassifier(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]. |
sklearn.ensemble._weight_boosting.AdaBoostClassifier(1)_algorithm | "SAMME.R" |
sklearn.ensemble._weight_boosting.AdaBoostClassifier(1)_base_estimator | null |
sklearn.ensemble._weight_boosting.AdaBoostClassifier(1)_learning_rate | 1.0 |
sklearn.ensemble._weight_boosting.AdaBoostClassifier(1)_n_estimators | 50 |
sklearn.ensemble._weight_boosting.AdaBoostClassifier(1)_random_state | 1113 |
0.7291 ± 0.014 Per class Cross-validation details (10-fold Crossvalidation)
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0.1679 ± 0.0136 Cross-validation details (10-fold Crossvalidation)
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0.057 ± 0.001 Cross-validation details (10-fold Crossvalidation)
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0.0198 ± 0 Cross-validation details (10-fold Crossvalidation)
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0.0195 ± 0 Cross-validation details (10-fold Crossvalidation)
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0.1949 ± 0.014 Cross-validation details (10-fold Crossvalidation)
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65196 Per class Cross-validation details (10-fold Crossvalidation) |
0.1949 ± 0.014 Cross-validation details (10-fold Crossvalidation)
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5.9777 ± 0.001 Cross-validation details (10-fold Crossvalidation)
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1.0115 ± 0.0002 Cross-validation details (10-fold Crossvalidation)
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0.0989 ± 0 Cross-validation details (10-fold Crossvalidation)
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0.0994 ± 0 Cross-validation details (10-fold Crossvalidation)
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1.0051 ± 0.0002 Cross-validation details (10-fold Crossvalidation)
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0.0815 ± 0.0052 Cross-validation details (10-fold Crossvalidation)
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