I've seen several people doing prefiltering based on correlation coefficients. But would it be ok to find best features using GradientBoostingRegressor and then use those to train a network?
Is there any chance I could implement such computation within the Network?
My data consists of 40 thousand features and around 60 samples. All of them numerical and the output is also numerical (the age of the person). It is a regression problem.
I am experiencing "the curse of dimensionality" and wanted to know what would be the best way to address feature selection. Filtering methods and PCA didn't give optimal results.