Analysis of correlation based dimension reduction methods - Shin, Yong Joon; Park, Cheong Hee (Zielona Góra: Uniwersytet Zielonogórski)
Dimension reduction is an important topic in data mining and machine learning. Especially dimension reduction combined with feature fusion is an effective preprocessing step when the data are described by multiple feature sets. Canonical Correlation Analysis (CCA) and Discriminative Canonical Correlation Analysis (DCCA) are feature fusion methods based on correlation
Keywords: canonical correlation analysis; dimension reduction; discriminative canonical correlation analysis; feature fusion; linear discriminant analysis