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In glmnet.py, there's a restriction on the dtype. see below. I'm running with very large dataset, which leads to an extremely big matrix. I'm wondering if there's any specific reason why this has to be float64?
if not( isinstance(x, scipy.sparse.csc.csc_matrix) ):
if not( isinstance(x, scipy.ndarray) and x.dtype == 'float64'):
raise ValueError('x input must be a scipy float64 ndarray')
else:
if not (x.dtype == 'float64'):
raise ValueError('x input must be a float64 array')
if not( isinstance(y, scipy.ndarray) and y.dtype == 'float64'):
raise ValueError('y input must be a scipy float64 ndarray')
The text was updated successfully, but these errors were encountered:
In glmnet.py, there's a restriction on the dtype. see below. I'm running with very large dataset, which leads to an extremely big matrix. I'm wondering if there's any specific reason why this has to be float64?
The text was updated successfully, but these errors were encountered: