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		Ling YU,Tiejun WU.[en_title][J].Control Theory and Technology,2006,4(3):257~260.[Copy]

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LingYU,TiejunWU
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Received:September 09, 2005Revised:March 29, 2006

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Boosting the partial least square algorithm for regression modelling

Ling YU, Tiejun WU

(Department of Control Science and Engineering, Zhejiang University, Hangzhou Zhejiang 310027, China)

Abstract:

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.

Key words: Boosting Partial least square (PLS) Multivariate regression Generalization