I'm looking at Fisher's LDA on various datasets on UCI ML repository and trying to see where LDA might perform badly. One reason I can think of is if the data distribution is not a multi-variate normal distribution. This is from the fact I read in a book where you apply LDA on multivariate normal distribution. Is that thought process correct? When might LDA give bad results?