Comments (6)
marcotcr
commented on August 26, 2024
Yeah, this is something I thought I was going to add a few weeks back. I already have code for it, it's just a matter of cleaning it up and plugging it with the library. I won't promise any specific date, but it is something I hope to have in the near future.
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TKlerx
commented on August 26, 2024
Hi,
thanks for the very nice library.
I guess you are quite busy, but is there any update on the model explanation? Or can I help somehow, e.g. by testing or trying to clean up?
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marcotcr
commented on August 26, 2024
I have code for it for both text and tabular data, but no time to clean it up at the moment, unfortunately.
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ccmien
commented on August 26, 2024
Hi~ any progress? Need any helper?
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AlJohri
commented on August 26, 2024
I think this is related to #11. Also happy to lend a hand if needed.
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marcotcr
commented on August 26, 2024
closed by #206
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Related Issues (20)
- Can LIME only be used for text classification tasks?
- How to explain prediction for a data with just a few features (from all features of training dataset)? HOT 2
- Trying to explaine a simple Neural Network using LIME HOT 1
- submodular pick
- ans = self.domain_mapper.map_exp_ids(self.local_exp[label_to_use], **kwargs) KeyError: 1
- Getting error when my predict_fn is actually a method from a class HOT 1
- `show_in_notebook` shows no bars
- importance score for all tokens
- Unexpected keyword argument 'progress_bar' for lime_image.LimeImageExplainer().explain_instance()
- Issues with LIME Implementation in Image Classification
- How to use lime with 3 dim time series data and lstm
- Distances derivation, explain_instance() method in Tabular LIME
- How to handle binary features
- RecurrentTabularExplainer for regression task
- Question: using LIME for text generation HOT 1
- LIME and multi-correlated variables
- update Python support
- Inverse scaling/ normalization to get actual unscaled values in explanation : Old issue but I made a way around
- Met the issue about TypeError when using lime_image.LimeImageExplainer()
- Saving the output of show_in_notebook as static image
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