Feature selection in K means clustering
The brute force approach is to try all different 380 possibilities.
The non brute force approach could be try to do your clustering with 19 features (all 20 solutions) and keeping the best one, then dropping one more, selecting the best of the 19... up to two classes.
I have a dataset with more than 20 columns. I want to find out which two variables contributes towards highest importance. How to do it?