AINeutralarXiv – CS AI · 14h ago7/10
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Regional Explanations: Bridging Local and Global Variable Importance
Researchers identify fundamental flaws in Local Shapley Values and LIME, two widely-used machine learning interpretation methods that fail to reliably detect locally important features. They propose R-LOCO, a new approach that bridges local and global explanations by segmenting input space into regions and applying global attribution methods within those regions for more faithful local attributions.