Kernel Generalized Canonical Correlation Analysis
نویسندگان
چکیده
A classical problem in statistics is to study relationships between several blocks of variables. The goal is to find variables of one block directly related to variables of other blocks. The Regularized Generalized Canonical Correlation Analysis (RGCCA) is a very attractive framework to study such a kind of relationships between blocks. However, RGCCA captures linear relations between blocks and to assess nonlinear relations we propose a kernel extension of RGCCA.
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ورودعنوان ژورنال:
- Computational Statistics & Data Analysis
دوره 90 شماره
صفحات -
تاریخ انتشار 2015