Variable Importance Plots (VIPs)

Fast approximate Shapley values in R

Explainable Machine Learning in Survival Analysis

SurvSHAP(t): Time-dependent explanations of machine learning survival models

Variable importance through targeted causal inference, with Alan Hubbard

🎯🎓 Generalized Targeted Learning Framework

Routines and data structures for using isarn-sketches idiomatically in Apache Spark

Stability Selection with Error Control

Perform inference on algorithm-agnostic variable importance

Perform inference on algorithm-agnostic variable importance in Python

Code for Variable Selection in Black Box Methods with RelATive cEntrality (RATE) Measures

Filter-based feature selection for mlr3

Code for the paper 'Variable Selection with Copula Entropy' published on Chinese Journal of Applied Probability and Statistics

We used different machine learning approaches to build models for detecting and visualizing important prognostic indicators of breast cancer survival rate. This repository contains R source codes for 5 steps which are, model evaluation, Random Forest further modelling, variable importance, decision tree and survival analysis. These can be a pipe…

🎯 🎲 Targeted Learning of the Causal Effects of Stochastic Interventions

📦 R/txshift: Efficient Estimation of the Causal Effects of Stochastic Interventions, with Corrections for Outcome-Dependent Sampling

Variable importance via oscillations

🎯 💯 Targeted Learning and Variable Importance for the Causal Effect of an Optimal Individualized Treatment Intervention

💫 🎯 Automatic identification of variable and interaction importance using basis functions and non-parametric estimation of interactions/effect modification using joint stochastic interventions.

Dimension Reduction Forests