Multiview partial least squares

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• 作者：Yi Mou^a ; ^{mouyi@whpu.edu.cn} ; Long Zhou^a ; Xinge You^b ; Yaling Lu^a ; Weizhen Chen^a ; Xu Zhao^a
• 关键词：Multiview data ; Partial least squares ; Regression
• 刊名：Chemometrics and Intelligent Laboratory Systems
• 出版年：2017
• 出版时间：15 January 2017
• 年：2017
• 卷：160
• 期：Complete
• 页码：13-21
• 全文大小：1168 K
• 卷排序：160

文摘

We have proposed a multiview learning based partial least squares. This model finds a series of direction vectors wi(i=1,..,n)wi(i=1,..,n), which guarantee covariance between response YY and weighted component ∑i=1NαiXiwi and pairwise correlation of component Xiwi(i=1,…,nXiwi(i=1,…,n reach maximum. We have also developed a solution to the proposed method. Convergence analysis is conducted in this paper.