I'm doing binary classification on 300Ksamples and 19 features. I employed RandomizedLogisticRegression() in scikit for feature selection. I'd like to know how can I find which features are selected by RandomizedLogisticRegression().
You should use the get_support
function:
from sklearn.datasets import load_iris
from sklearn.linear_model import RandomizedLogisticRegression
iris = load_iris()
X, y = iris.data, iris.target
clf = RandomizedLogisticRegression()
clf.fit(X,y)
print clf.get_support()
#prints [False True True True]
Alternatively, you can get the indices of the support features:
print clf.get_support(indices=True)
#prints [1 2 3]