Feature selection: Use feature selection as a form of dimensionality reduction when your data has dimensions that are not relevant to the problem you are trying to solve or if you have repeating information within dimensions. In these cases, simply remove the unnecessary dimensions.

Feature extraction: Use feature extraction for dimensionality reduction when you want to use most of the information from your data set, but need the information explained in fewer dimensions. Also, feature extraction will take care of some of the repeat information from your data.