Analysis of Care Ranks by Fuzzy c- Means with Maximizing Canonical Correlation Coefficients

Abstract

A new approach to canonical correlation analysis in which the Fuzzy c-Means clustering algorithm is simultaneously applied. Minimization of the within-group sum-of-squared-error and maximization of the canonical correlation coefficients yields memberships of fuzzy clusters and principal components of each cluster can be analyzed from a complex of statistical variables. The relation between ADL (activity of daily life) and care ranks of advanced aged persons is analyzed.