Seasonality changepoint detection does not seem to work with cross-validation for Silverkite about greykite

[KaixuYang]

Hi @julioasotodv thanks for the detailed example. Somehow the code ran without error on my machine (after I change cv_horizon to 5). I see you are using the Anaconda environment. What is the python version and pandas/sklearn version?

[julioasotodv]

Hi @KaixuYang, after some more testing (also on Mac, as I was using Windows before) it seems that my pandas version was the issue.

I was using pandas=1.3.3. After downgrading to pandas 1.2 (for instance, pandas=1.2.5) the issue goes away and CV results are not NaN anymore, so it looks like some pandas op in greykite\algo\changepoint\adalasso\changepoint_detector.py does not seem to play well with pandas>=1.3.

So downgrading to pandas 1.2 solves the issue, which is great to know.

Shall I keep this issue open or perhaps a PR in the meantime for modifying setup.py accordingly?

Thanks a lot

[KaixuYang]

Hi @julioasotodv thanks for the investigation. Actually the root cause of this issue is that this is a monthly data set, and since the number of potential changepoints are too many, it brings duplicates into the columns. Instead of forcing the pandas version to be 1.2, we would like to fix this issue so it will get along with pandas 1.3 as well. Could you help us submitting a PR to fix this? I think a reasonable fix would be that: in line 230 of greykite.algo.changepoint.adalasso, the changepoints contains duplicates. We want to eliminate the duplicates with the util function greykite.common.python_utils.unique_elements_in_list. Could you test if this resolves the problem? Thanks!

[julioasotodv]

Hi @KaixuYang, thank you for reaching out.

I understand the issue. However, there is not change in pandas 1.3 that should yield these two different behaviors as far as I know.

Will try to debug and search in pandas' changelogs before "hardcoding" a greykite.common.python_utils.unique_elements_in_list patch, just to make sure there would not be any side effects.

Thanks!

[KaixuYang]

Thanks @julioasotodv ! Yeah actually unique_elements_in_list should be a safe guard for the function even for the earlier versions of pandas, but we failed to put it there. It would be great to add it there so no duplicated columns are generated.

[KaixuYang]

Fixed in the next release.