KBinsDiscretizer : Support inverse_transform for encode other than ordinal
See original GitHub issueCurrently, we only support encode='ordinal'
in inverse_transform
. Since we’ve supported inverse_transform
in OnehotEncoder
, it’s natural to support inverse_transform
for encode='onehot'
and encode='onehot-dense'
. Store the fitted encoder will be a reasonable solution here. (See https://github.com/scikit-learn/scikit-learn/pull/11467#issuecomment-403995635)
Issue Analytics
- State:
- Created 5 years ago
- Comments:11 (8 by maintainers)
Top Results From Across the Web
sklearn.preprocessing.KBinsDiscretizer
Ignored features are always stacked to the right. 'ordinal': Return the bin identifier encoded as an integer value. strategy{'uniform', 'quantile' ...
Read more >How to use KBinsDiscretizer to make continuous data into ...
I am working on a ML algorithm in which I tried to convert the continuous target values into small bins to understand the...
Read more >KBinsDiscretizer encodes wrong bin identifiers for quantile ...
When KBinsDiscretizer is used with quantile strategy to create ordinal encoding the created ID doesn't match the quantile identifier.
Read more >cuML API Reference — cuml 22.10.00 documentation
An nvcategory based implementation of ordinal label encoding ... from cuml.preprocessing import KBinsDiscretizer >>> import cupy as cp >>> X = [[-2, 1,...
Read more >17: Scikit-learn 14: Preprocessing 14: KBinsDiscretizer()
The video discusses the code to implement KBinsDiscretizer () in ... notebook 00:34 - Data 00:57 - KBinsDiscretizer : encode =' ordinal ', ......
Read more >
Top Related Medium Post
No results found
Top Related StackOverflow Question
No results found
Troubleshoot Live Code
Lightrun enables developers to add logs, metrics and snapshots to live code - no restarts or redeploys required.
Start Free
Top Related Reddit Thread
No results found
Top Related Hackernoon Post
No results found
Top Related Tweet
No results found
Top Related Dev.to Post
No results found
Top Related Hashnode Post
No results found
It’s not uncommon to set attributes in fit? I don’t think it will cause a test failure. Maybe you can submit a PR for us to review.
Resolved in #11489