哪些功能选择fit_transform？

Question

I'm selecting features using LinearSVC. All the features are binaries. This is how it looks like:

In>  X0.shape
Out> (6876299, 49)
In>  lsvc = LinearSVC(C=0.01, penalty="l1", dual=False)
In>  X_new = lsvc.fit_transform(X0, y0)
In>  X_new.shape
Out> (6876299, 41)

My problem is very simple, but I haven't found any specific solution. How am I supposed to know which features have been selected by fit_transform?

Thks!

Answer 1

You can take a look at lsvc.coef_ . The features with non-zero coefficients will be the ones that have been chosen. For example the following will give you a mask of all non-zero features:

>>> from sklearn.datasets import load_iris
>>> iris = load_iris()
>>> X, y = iris.data, iris.target
>>> X.shape
(150, 4)

>>> lsvc = LinearSVC(C=0.01, penalty="l1", dual=False)
>>> X_new = lsvc.fit_transform(X, y)
>>> X_new.shape
(150, 3)

>>> lsvc.coef_
array([[ 0.        ,  0.21680351, -0.28727891,  0.        ],
       [ 0.        , -0.09186784,  0.        ,  0.        ],
       [-0.03501512, -0.17022421,  0.13485806,  0.        ]])

>>> ~np.all(lsvc.coef_==0, axis=0)
array([ True,  True,  True, False], dtype=bool)