I have performed PCA on my data set and found out that 95% of variability has been covered by the first three principal components. I wanted to perform a logistic regression on the data set. What do I do now?
Train the model as usual with those three components. We have to do the same thing on test data too. Your classification job can be done.
Note: By training a model with PCA components. You don't get feature importance. If that is fine, you can proceed with those three components. Else, those components can be useful for just visualization purpose.