Comments (1)
Hi Simon,
Thank you very much for your contribution, this helps indeed!
Similar to what you suggested, I enabled the function check_array(X). I did not use it within the try catch syntax but enabled checking by default - calling check_array is extremely fast so this won't change performance. In our case we want to allow for Nans as input, so i am using check_array(..., force_all_finite=False). This also still allows the case where all inputs are set to np.nan, but have correct shapes etc., as this is the standard sklearn error handling.
Thanks a lot!
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Related Issues (20)
- Default model supports only 100 dimensions? HOT 2
- Can you give an index list of the 18 datasets used for Table 1? HOT 1
- What should I do to reproduce your results? HOT 2
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