Compute SHAP values for your tree-based models using the TreeSHAP algorithm
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Updated
Jun 9, 2024 - R
Compute SHAP values for your tree-based models using the TreeSHAP algorithm
An R package for computing asymmetric Shapley values to assess causality in any trained machine learning model
R package for SHAP plots
Weighted Shapley Values and Weighted Confidence Intervals for Multiple Machine Learning Models and Stacked Ensembles
Tools to Support Relative Importance Analysis
Purely presence-only species distribution modeling with isolation forest and its variations such as Extended isolation forest and SCiForest.
This repository consists the supplemental materials of the paper "Decomposition of Expected Goal Models: Aggregated SHAP Values for Analyzing Scoring Potential of Player/Team".
Application on Markov Chain and Removal Effect (Attribution Modeling)
use XGBoost and Adaboost to predict heart disease and use SHAP to explain the potential factors behind the result.
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