How to Explain the Prediction of a Machine Learning Model?
Read OriginalThis article discusses the critical need for explainability in machine learning models, particularly in high-stakes domains like finance, healthcare, and criminal justice. It introduces key concepts of model interpretability, such as simulatability and decomposability, and begins a technical review of interpretable models, starting with linear regression and coefficient analysis.
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