1. Fisher’s Linear Discriminant  Find a direction and project all data points onto that direction such that:  The points in the same class are as close as possible  The centers of these two classes are as far as possible

2. Fisher’s Linear Discriminant

3. Variance between-class The centers of these two classes are as far as possible

4. Variances within-class The points in the same class are as close as possible

5. Rayleigh Coefficient  Rayleigh coefficient with respect to is defined as  Linear Fisher ’ s discriminant is generated by maximizing the Rayleigh coefficient  How about the nonlinear Fisher ’ s discriminant?