PCA on Neural Networks dimensions reduction? The dataset which was extracted from the database consists of more than 50         columns, I call these columns dimensions, can I call them dimensions?
Obviously, I have to do dimension reduction on them. But since PCA like algorithms often do axis rotating to generate some new axises. I don't think I will PCA algorithm in dimensions reduction. So I calculated the correlations between these columns(parameters), and filtered these who has a high value and some other rules. So can I still call it dimensions reduction? Since I only did some parameters filtering
The reason I don't use PCA like algorithms is because I want to implement Neural Network classification, and I need the real parameters.


Please comment on these, anything even criticizing is welcomed.
The approach you use to do dimensions reduction is agnostic to the method you use for classification. You can use PCA to preprocess your data before to train any type of classifier, including artificial neural networks if that's what you want to use.