How to define the features that bring more variance?

I have a dataset with 10 column, that are my features, and 1732 row that are my registrations. This registration are divided in 15 classes, so I have several registration for every class in my dataset. My goal is to define what is the most important feature, the one that brings more variance between classes.

I'm trying to use PCA, but because of the several registration for every classes it's difficult to find the right way of use oof this method.

Is there another method that can I use?

Topic variance pca

Category Data Science

1
answered at

I don't know any direct method for your problem. But i suggest to use Forward Selection idea for it. I mean you can classify based on each column of your table. Then see which feature gives you best accuracy. The column with the most accuracy rate is your most important feature to your classify problem.

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