LDA for high dimension small sample size data

Linear discriminant analysis when the data dimensionality is high and sample size is much smaller

Description

For medical imaging/ biological data where typically data dimensionality is huge typical LDA applications fail on account of attempting to invert an impossibly large matrix. This can be remedied using the kernel trick. The current file attempts to do this.

 I have made an attempt to put in appropriate comments in the code and this code is inspired by several previous codes submitted on matlab central. I could not find an equivalent very easily. Hence I have submitted this file so that other biology related people here do not have to go through the pain of reimplementing it

• MATLAB release: MATLAB 7.8 (R2009a)