scikit-learn-contrib/category_encoders

FloatingPointError: underflow encountered in exp

CoteDave opened this issue · 2 comments

catboost version: 2.5.1
numpy version: 1.23.3

image

t_encoder= TargetEncoder(min_samples_leaf=20, smoothing=10)
t_encoded = t_encoder.fit_transform(new_xy_test_dummy[[cat_col]].astype(str), new_xy_test_dummy[[target_col]], cols = [cat_col])

No nans...

Same data seems to work with WOE encoder. Encountered the problem only with TargetEncoder:
w_encoder= WOEEncoder()
w_encoded = w_encoder.fit_transform(new_xy_test_dummy[[cat_col]].astype(str), new_xy_test_dummy[[target_col]], cols = [cat_col]) = works!

Any Ideas ?

Thanks !

can you please provide some data in order to reproduce this and also format your code as code (for better readability)

glevv commented

There is an easy and long awaited fix.

But we still need data example (or specific values, in this case very small ones) for testing purposes.