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With sklearn Version 0.22.1 a linear regression with negative sample weights fails with the following (unclear) error message.
Would be helpful if (e.g. _check_sample_weight) checks for negative weights and raises an appropriate error message.
File "C:\Users\gm889704\.conda\envs\gm\lib\site-packages\sklearn\pipeline.py", line 354, in fit
self._final_estimator.fit(Xt, y, **fit_params)
File "C:\Users\gm889704\.conda\envs\gm\lib\site-packages\sklearn\linear_model\_base.py", line 533, in fit
linalg.lstsq(X, y)
File "C:\Users\gm889704\.conda\envs\gm\lib\site-packages\scipy\linalg\basic.py", line 1157, in lstsq
a1 = _asarray_validated(a, check_finite=check_finite)
File "C:\Users\gm889704\.conda\envs\gm\lib\site-packages\scipy\_lib\_util.py", line 246, in _asarray_validated
a = toarray(a)
File "C:\Users\gm889704\.conda\envs\gm\lib\site-packages\numpy\lib\function_base.py", line 499, in asarray_chkfinite
"array must not contain infs or NaNs")
ValueError: array must not contain infs or NaNsMetadata
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