Boosting the partial least square algorithm for regression modelling

被引：1
|
作者：
Ling Yu
Tiejun Wu
机构：
[1] Zhejiang University,Department of Control Science and Engineering
来源：
Journal of Control Theory and Applications | 2006年 / 4卷 / 3期
关键词：
Boosting; Partial least square (PLS); Multivariate regression; Generalization;
D O I：
10.1007/s11768-006-5231-z
中图分类号：
学科分类号：
摘要：
Boosting algorithms are a class of general methods used to improve the general performance of regression analysis. The main idea is to maintain a distribution over the train set. In order to use the given distribution directly, a modified PLS algorithm is proposed and used as the base learner to deal with the nonlinear multivariate regression problems. Experiments on gasoline octane number prediction demonstrate that boosting the modified PLS algorithm has better general performance over the PLS algorithm.
引用
收藏
页码：257 / 260
页数：3
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