thank you for the amazing video! so what do you think are the main differences for global interpretations of LIME and SHAP methods? also this is the first time I'm seeing that LIME is used as a global "interpretator". why do you think that LIME is mostly used for local points whereas it can be aggregated just like SHAP? thanks!
Great questions! SHAP is used to estimate Shapley values. So it inherits properties that are useful for understanding and comparing models. See these videos on the theory behind Shapley values for ML: ruclips.net/video/UJeu29wq7d0/видео.html ruclips.net/video/b9qqbFudVhI/видео.html I think LIME is not used in this way for two reasons: 1) it is slower than SHAP (especially TreeSHAP) to get individual feature weights. This can make it time-consuming to aggregate and analyse many instances. 2) There are no built-in functions to create aggregated plots for LIME like you see in the SHAP package. In general, LIME has fallen out of favour due to the solid theory and speed of SHAP values. So perhaps the creators have decided not to develop the method further.
thank you my dear can you show me another video which completed relate yearand week bilstm and it depends with many column like temperature , turbidty , ph and so on
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Super amazing ,clearly explained and really helpful video 🔥 , keep it up 👍
@@omprakashpatel6700 thanks! Will do :)
thank you for the amazing video! so what do you think are the main differences for global interpretations of LIME and SHAP methods? also this is the first time I'm seeing that LIME is used as a global "interpretator". why do you think that LIME is mostly used for local points whereas it can be aggregated just like SHAP? thanks!
Great questions! SHAP is used to estimate Shapley values. So it inherits properties that are useful for understanding and comparing models. See these videos on the theory behind Shapley values for ML:
ruclips.net/video/UJeu29wq7d0/видео.html
ruclips.net/video/b9qqbFudVhI/видео.html
I think LIME is not used in this way for two reasons:
1) it is slower than SHAP (especially TreeSHAP) to get individual feature weights. This can make it time-consuming to aggregate and analyse many instances.
2) There are no built-in functions to create aggregated plots for LIME like you see in the SHAP package.
In general, LIME has fallen out of favour due to the solid theory and speed of SHAP values. So perhaps the creators have decided not to develop the method further.
thank you my dear can you show me another video which completed relate yearand week bilstm and it depends with many column like temperature , turbidty , ph and so on
I will see what I can do. However, I will take a break from youtube for a while :)
Hi, your audio volume is slightly lesser than other normal videos in youtube. Thanks
Hi Alok, thank you for pointing that out. Still working out the kinks. Will sort that out in future videos.