sklearn.preprocessing.binarize¶
- sklearn.preprocessing.binarize(X, threshold=0.0, copy=True)[source]¶
Boolean thresholding of array-like or scipy.sparse matrix
Read more in the User Guide.
Parameters: X : {array-like, sparse matrix}, shape [n_samples, n_features]
The data to binarize, element by element. scipy.sparse matrices should be in CSR or CSC format to avoid an un-necessary copy.
threshold : float, optional (0.0 by default)
Feature values below or equal to this are replaced by 0, above it by 1. Threshold may not be less than 0 for operations on sparse matrices.
copy : boolean, optional, default True
set to False to perform inplace binarization and avoid a copy (if the input is already a numpy array or a scipy.sparse CSR / CSC matrix and if axis is 1).
See also
sklearn.preprocessing.Binarizer, using, sklearn.pipeline.Pipeline