sklearn.utils
.safe_mask#
- sklearn.utils.safe_mask(X, mask)[source]#
Return a mask which is safe to use on X.
- Parameters:
- X{array-like, sparse matrix}
Data on which to apply mask.
- maskarray-like
Mask to be used on X.
- Returns:
- maskndarray
Array that is safe to use on X.
Examples
>>> from sklearn.utils import safe_mask >>> from scipy.sparse import csr_matrix >>> data = csr_matrix([[1], [2], [3], [4], [5]]) >>> condition = [False, True, True, False, True] >>> mask = safe_mask(data, condition) >>> data[mask].toarray() array([[2], [3], [5]])