Nonlinear formulations of canonical correlation analysis and discriminant analysis are given, and it is shown that both reduce to the same eigen problem. Both problems can be regarded as a method to represent the probabilistic structure of data into a topological space(L-dimensional Euclindean space).Further, the usual linear cases are interpreted as linear approxi-mations of the nonlinear cases.