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ifisinstance(feature_matrix, np.ndarray):
feature_matrix=csr_matrix(feature_matrix)
ifnotisinstance(feature_matrix, csr_matrix):
raiseValueError(
"The feature matrix should be convertible to type ""scipy.sparse.csr.csr_matrix."
)
We're casting all feature matrices to sparse matrix. This might be inefficient in some cases when compared to using a dense matrix.
Why was this format chosen?
The text was updated successfully, but these errors were encountered:
https://github.com/asreview/asreview/blob/25ce8540a9c7e006c100b0da3617bc342c3597d3/asreview/project.py#L390C1-L397C14
We're casting all feature matrices to sparse matrix. This might be inefficient in some cases when compared to using a dense matrix.
Why was this format chosen?
The text was updated successfully, but these errors were encountered: