Here is my Code for feature selection method in Python:
from sklearn.svm import LinearSVC from sklearn.datasets import load_iris iris = load_iris() X, y = iris.data, iris.target X.shape (150, 4) X_new = LinearSVC(C=0.01, penalty="l1", dual=False).fit_transform(X, y) X_new.shape (150, 3)
But after getting new X(dependent variable - X_new), How do i know which variables are removed and which variables are considered in this new updated variable ? (which one removed or which three are present in data.)
Reason of getting this identification is to apply the same filtering on new test data.