I have a data set with dimension of 330 * 45000 ( 330 samples and 45000 features : reads in peaks)
I am looking for a way to select best features for binary classification. so far I only chose feature with
covariance higher than 0.5 or less than -0.5 and reduced dimension to 14000. but I know I should reduce dimension furthermore , I'm not sure if I can use
randomforest at this stage, do you have any suggestions or tips ?