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 | 14364 |
0.7873 ± 0.0112 Per class Cross-validation details (10-fold Crossvalidation)
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0.7233 ± 0.0081 Per class Cross-validation details (10-fold Crossvalidation)
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0.4186 ± 0.0171 Cross-validation details (10-fold Crossvalidation)
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-0.0534 ± 0.0004 Cross-validation details (10-fold Crossvalidation)
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0.4957 ± 0.0002 Cross-validation details (10-fold Crossvalidation)
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0.4801 ± 0 Cross-validation details (10-fold Crossvalidation)
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0.7276 ± 0.0079 Cross-validation details (10-fold Crossvalidation)
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20000 Per class Cross-validation details (10-fold Crossvalidation) |
0.724 ± 0.0082 Per class Cross-validation details (10-fold Crossvalidation)
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0.7276 ± 0.0079 Cross-validation details (10-fold Crossvalidation)
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0.971 ± 0.0001 Cross-validation details (10-fold Crossvalidation)
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1.0327 ± 0.0003 Cross-validation details (10-fold Crossvalidation)
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0.4899 ± 0 Cross-validation details (10-fold Crossvalidation)
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0.4958 ± 0.0002 Cross-validation details (10-fold Crossvalidation)
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1.012 ± 0.0003 Cross-validation details (10-fold Crossvalidation)
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0.7043 ± 0.0086 Cross-validation details (10-fold Crossvalidation)
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