Non-Linear Canonical Correlation Analysis Using Alpha-Beta Divergence

Non-Linear Canonical Correlation Analysis Using Alpha-Beta Divergence

We propose a generalized method of the canonical correlation analysis using Alpha-Beta divergence, called AB-canonical analysis (ABCA). From observations of two random variables, x ∈ R and y ∈ R, ABCA finds directions, wx ∈ R and wy ∈ R, such that the AB-divergence between the joint distribution of (w xx,w T y y) and the product of their marginal distributions is maximized. The number of signif...

Non-linear Canonical Correlation Analysis using a RBF networks

A non-linear version of the multivariate statistical technique of canonical correlation analysis (CCA) is proposed through the integration of a radial basis function (RBF) network. The advantage of the RBF network is that the solution of linear CCA can be used to train the network and hence the training effort is minimal. Also the canonical variables can be extracted simultaneously. It is shown...

Canonical Divergence Analysis

We aim to analyze the relation between two random vectors that may potentially have both different number of attributes as well as realizations, and which may even not have a joint distribution. This problem arises in many practical domains, including biology and architecture. Existing techniques assume the vectors to have the same domain or to be jointly distributed, and hence are not applicab...

Canonical correlation analysis using within-class coupling

0167-8655/$ see front matter 2010 Elsevier B.V. A doi:10.1016/j.patrec.2010.09.025 q The work of O. Kursun was supported by Scienti nation Unit of Istanbul University under the grant YA ⇑ Corresponding author. Tel.: +90 212 473 7070/17 E-mail addresses: [email protected] (O. Kurs Alpaydin), [email protected] (O.V. Favorov). Fisher’s linear discriminant analysis (LDA) is one of the most ...

Predicting Atmospheric Parameters using Canonical Correlation Analysis