Bagging equalizes influence.
Bagging constructs an estimator by averaging predictors trained on bootstrap samples. Bagged estimates almost consistently improve on the original predictor. It is thus important to understand the reasons for this success, and also for the occasional failures. It is widely believed that bagging is e...
| Τόπος έκδοσης: | Machine learning. 55, 3 (2004). |
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| Κύριος συγγραφέας: | |
| Μορφή: | Άρθρο |
| Γλώσσα: | English |
| Θέματα: |