--- title: When Shapley Values Break: A Guide to Robust Model... description: Shapley values are widely used for model explainability but can produce misleading results when features are correlated. When duplicate or highly correlated... canonical: https://daily.dev/posts/when-shapley-values-break-a-guide-to-robust-model-explainability-qnyk8s3p1 twitter:card: summary_large_image twitter:site: @dailydotdev og:type: website og:site_name: daily.dev og:title: When Shapley Values Break: A Guide to Robust Model Explainability | daily.dev og:description: Shapley values are widely used for model explainability but can produce misleading results when features are correlated. When duplicate or highly correlated... og:url: https://daily.dev/posts/when-shapley-values-break-a-guide-to-robust-model-explainability-qnyk8s3p1 og:image: https://api.daily.dev/og/posts/qNYK8s3P1.png og:image:alt: When Shapley Values Break: A Guide to Robust Model Explainability og:image:width: 1200 og:image:height: 630 og:locale: en --- > ## Documentation Index > Fetch the complete documentation index at: https://daily.dev/llms.txt > Use this file to discover all available pages before exploring further. # When Shapley Values Break: A Guide to Robust Model Explainability **[Towards Data Science](https://daily.dev/sources/tds)** · 10 min read · 1 upvotes · 0 comments ## Summary Shapley values are widely used for model explainability but can produce misleading results when features are correlated. When duplicate or highly correlated features exist, the signal gets diluted across them due to the Symmetry Axiom, hiding true model drivers. Two solutions address this: grouping correlated features into single concepts and using iterative greedy selection that conditions on previously selected features to eliminate redundancy. These methods were validated in clinical healthcare models with hundreds of correlated features and outperformed vanilla Shapley values in blind evaluations. ## Full article daily.dev links to this article rather than hosting it. Read it at the original source: ## Similar posts on daily.dev - [Introducing ShaTS: A Shapley-Based Method for Time-Series Models](https://daily.dev/posts/introducing-shats-a-shapley-based-method-for-time-series-models-yrudpraqf) · Towards Data Science · 0 upvotes · 0 comments - [Explaining Time-Series Forecasts with Exact Shapley Values \(ahead::dynrmf with external regressors applied to scenarios\)](https://daily.dev/posts/explaining-time-series-forecasts-with-exact-shapley-values-ahead-dynrmf-with-external-regressors-a-b5p5dlgvj) · R-bloggers · 0 upvotes · 0 comments - [Week 8: The Week I Stopped Chasing Better Models and Started Asking Why](https://daily.dev/posts/week-8-the-week-i-stopped-chasing-better-models-and-started-asking-why-pwbqjyd1n) · Medium · 0 upvotes · 0 comments - [3 Ways to Enhance Your AI Model’s Interpretability](https://daily.dev/posts/3-ways-to-enhance-your-ai-model-s-interpretability-swviiuyl1) · Machine Learning Mastery · 0 upvotes · 0 comments - [Effective Use of Uncorrelated Random Variables in LLM Applications](https://daily.dev/posts/effective-use-of-uncorrelated-random-variables-in-llm-applications-iz9fw2asn) · PromptLayer Blog · 0 upvotes · 0 comments --- Tags: [#machine-learning](https://daily.dev/tags/machine-learning), [#python](https://daily.dev/tags/python), [#data-science](https://daily.dev/tags/data-science), [#explainable-ai](https://daily.dev/tags/explainable-ai) [View this post on daily.dev](https://daily.dev/posts/when-shapley-values-break-a-guide-to-robust-model-explainability-qnyk8s3p1) ```json {"@context":"https://schema.org","@graph":[{"@type":"Organization","@id":"https://daily.dev/#organization","name":"daily.dev","url":"https://daily.dev","logo":{"@type":"ImageObject","url":"https://daily.dev/apple-touch-icon.png","width":180,"height":180},"sameAs":["https://twitter.com/dailydotdev","https://github.com/dailydotdev","https://www.linkedin.com/company/daily-dev-ltd"]},{"@type":"WebSite","@id":"https://daily.dev/#website","url":"https://daily.dev","name":"daily.dev","publisher":{"@id":"https://daily.dev/#organization"},"potentialAction":{"@type":"SearchAction","target":{"@type":"EntryPoint","urlTemplate":"https://daily.dev/search?q={search_term_string}"},"query-input":"required name=search_term_string"}}]} {"@context":"https://schema.org","@type":"TechArticle","headline":"When Shapley Values Break: A Guide to Robust Model Explainability","url":"https://daily.dev/posts/when-shapley-values-break-a-guide-to-robust-model-explainability-qnyk8s3p1","mainEntityOfPage":{"@type":"WebPage","@id":"https://daily.dev/posts/when-shapley-values-break-a-guide-to-robust-model-explainability-qnyk8s3p1"},"datePublished":"2026-01-15T17:12:18.825Z","dateModified":"2026-01-15T17:12:39.973Z","description":"Shapley values are widely used for model explainability but can produce misleading results when features are correlated. 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