Explainable Machine Learning in Survival Analysis
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Updated
Apr 16, 2024 - R
Explainable Machine Learning in Survival Analysis
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
Efficient R implementation of SHAP
Weighted Shapley Values and Weighted Confidence Intervals for Multiple Machine Learning Models and Stacked Ensembles
Implementation of the mSHAP algorithm for explaining two-part models, as described by Matthews and Hartman (2021).
Wrapper for shapjs node package for easy force plots in R without Python dependencies
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