harris-chris/joint-shapley-values
Source code for the Joint Shapley values: a measure of joint feature importance
This helps data scientists and machine learning engineers understand which combinations of features are most important to their model's predictions. It takes in a trained predictive model and its input data, then outputs a score for individual features and groups of features, revealing their joint influence. This is for professionals who build and interpret machine learning models and need to explain their behavior.
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Use this if you need to determine not just the importance of individual factors, but also how groups of factors together influence your predictive model's outcomes.
Not ideal if you are a business user looking for a simple, non-technical explanation of model predictions without diving into feature importance methodologies.
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Sep 14, 2021
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