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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
-
Binarizer
- Performs binarization using the
Transformer
API (e.g. as part of a preprocessingsklearn.pipeline.Pipeline
).
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sklearn.preprocessing.binarize()
2017-01-15 04:26:51
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