Observing Alternative Feature Importance Techniques

TL;DR Original List with yet-to-be implemented FE algorithms in https://github.com/parrt/random-forest-importances/issues/54

Seeing https://github.com/interpretml/interpret/issues/364 and https://github.com/interpretml/interpret/issues/218 I do notice that some of the feature importance algorithms are not on the list, particularly LOFO, Morris and "Unbiased" feature importance. Might wanna check those out?

Bonus: this visualization notebook exists https://github.com/shionhonda/feature-importance

Currently these are not in the ReadME:

• LOFO https://github.com/aerdem4/lofo-importance
• Permutation https://github.com/nestordemeure/permutationImportance
• "Unbiased" https://github.com/ZhengzeZhou/unbiased-feature-importance

Unsure if they have alternative name:

• LIME being similar to SHAP https://github.com/marcotcr/lime
• Gini https://github.com/shionhonda/feature-importance
• Split https://github.com/shionhonda/feature-importance

How are they different (missing data test vs prioritization, significant correlation)?