After applying PCA to reduce the number of features, I am using a DecisionTreeClassifier for a ML problem
Why would it change? I thought the initial split was made on a feature to "produce the purest subsets (weighted by their size)". Acting on the same training set, why would that change?
Thanks in advance for any help.