抄録
We propose a new, robust boosting method by using a siginoidal function as a loss function. In deriving the method, the stagewise additive modelling methodology is blended with the gradient descent algorithms. Based on intensive numerical experiments, we show that the proposed method is actually better than AdaBoost and other regularized method in test error rates in the case of noisy, mislabeled situation.
| 本文言語 | English |
|---|---|
| ページ（範囲） | 182-196 |
| ページ数 | 15 |
| ジャーナル | Journal of the Operations Research Society of Japan |
| 巻 | 47 |
| 号 | 3 |
| DOI | |
| 出版ステータス | Published - 2004 9月 |
| 外部発表 | はい |
ASJC Scopus subject areas
- 決定科学（全般）
- 経営科学およびオペレーションズ リサーチ