Yesterday I asked this question in which I had 180 subjects with 500 features each. While I was sure that dimensional-reduction is a must in this case (500 features), most of the answers I got said that 500 are not too many.
So, My question is: Is there any rule of thumb when one should use dimensional-reduction before the classifier? How many features is too many? (I guess it is depends upon the ratio between the number of subjects and features. Isn't it?)