GitHub - shap shap: A game theoretic approach to explain the output of . . . SHAP (SHapley Additive exPlanations) is a game theoretic approach to explain the output of any machine learning model It connects optimal credit allocation with local explanations using the classic Shapley values from game theory and their related extensions (see papers for details and citations)
SHAP : A Comprehensive Guide to SHapley Additive exPlanations SHAP (SHapley Additive exPlanations) has a variety of visualization tools that help interpret machine learning model predictions These plots highlight which features are important and also explain how they influence individual or overall model outputs
An Introduction to SHAP Values and Machine Learning Interpretability SHAP values can help you see which features are most important for the model and how they affect the outcome In this tutorial, we will learn about SHAP values and their role in machine learning model interpretation
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Using SHAP values and IntegratedGradients for cell type classification . . . Using SHAP values and IntegratedGradients for cell type classification interpretability # Previously we saw semi-supervised models, like SCANVI being used for tasks like cell type classification, enabling researchers to uncover complex biological patterns
JABE22 SHAP-Interpreter: SHAP Molecular Interpreter - GitHub The SHAP Molecular Interpreter is an interactive web application designed to bridge the gap between machine learning model outputs and chemical understanding It translates raw SHAP importance values into actionable chemical insights for chemists and medicinal chemists
2025 Shap derailment - Wikipedia The 2025 Shap derailment occurred on 3 November 2025 when a passenger train operated by Avanti West Coast ran into a landslide obstructing the West Coast Main Line at Shap Rural, Cumbria, England