Edge 257: Local Model-Agnostic Interpretability Methods
Was this email forwarded to you? Sign up here Edge 257: Local Model-Agnostic Interpretability MethodsLocal model-agnostic interpretability, IBMs ProfWeight research and the InterpretML framework.In this issue:
💡 ML Concept of the Day: Local Model-Agnostic Interpretability MethodsThe last few issue of this series have focused on global model-agnostic interpretability methods which try to extrapolate explanations about the complete behavior of an ML model. Local model-agnostic methods provide an alternative to its global counterpart by focusing on explaining individual predictions. In simple terms, local-method help to answer the following question: “for this particular example, why did the model make this particular decision?” A practical way to think about the utility of global vs. local method is monitoring vs. debugging. While global-methods are useful to regularly monitor the behavior of a ML model, local-methods are more effective when comes to debug specific behaviors. In the spectrum of local ML interpretability, there are several methods that are quite relevant:... Subscribe to TheSequence to read the rest.Become a paying subscriber of TheSequence to get access to this post and other subscriber-only content. A subscription gets you:
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