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} of 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.
- thresholdfloat, default=0.0
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.
- copybool, 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).
- Returns
- X_tr{ndarray, sparse matrix} of shape (n_samples, n_features)
The transformed data.