The pooled covariance matrix of TRAINING must be positive definite. (lda classifier)

Question

I have a problem with classification (LDA classifier ).

I have 80 samples of training data (80x100) and 15 samples of testing data (15x100). classify function returns: The covariance matrix of each group in TRAINING must be positive definite.

Answer 1

Without knowing how your data looks like, all I can do is to suggest you a few solutions that may solve your problem. A non positive definite convariance matrix can be produced by many different factors:

• linear dependence between two or more columns (you can get rid of as many columns that produce linear dependence as possible)
• non-stationary data (in this case, you can use differences instead of levels because they grant stationarity)
• columns with highly mismatching magnitude, for example a column with very big values and another one with very small values (rescale your columns so that all of them have approximately the same magnitude).