How to find which are all 'X' features/dimensions are selected/deselected by - LDA dimensionality reduction technique

Question

I was working on LDA dimensianality reduction technique and applied this technique in Iris data set. After applying LDA, my 4 features got reduced to only 2 features.

Now, I would like to know what are those 2 features which got selected/deselected by LDA technique.

Hope my question is clear. `

This is the code I tried from : https://www.geeksforgeeks.org/ml-linear-discriminant-analysis/

Answer 1

LDA does not select features, it tries to find a combination (linear in this case), to separate the data into different classes. To get the coefficients of these features, you can use this:

coefficients = lda.coef_

The order of the coefficients is the same order you used for the predictors, i.e., first value in coefficients represent the 1st feature (or column).