FernandoLpz/SHAP-Classification-example
This repository contains an example of how to implement the shap library to interpret a machine learning model.
This project helps data scientists and machine learning engineers understand why a machine learning model makes certain predictions. You provide your preprocessed dataset and a trained classification model, and it outputs explanations for the model's behavior. This allows you to interpret how different features influence the model's decisions.
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Use this if you need to explain the predictions of your machine learning classification models, especially in critical applications like healthcare or finance where transparency is key.
Not ideal if you are looking for a tool to build or train a machine learning model from scratch, as this project focuses solely on model interpretation.
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Jul 13, 2021
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