Variable Importance Plots (VIPs)

Fast approximate Shapley values in R

Explainable Machine Learning in Survival Analysis

Variable importance through targeted causal inference, with Alan Hubbard

🎯🎓 Generalized Targeted Learning Framework

Stability Selection with Error Control

Perform inference on algorithm-agnostic variable importance

Filter-based feature selection for mlr3

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

🎯 🎲 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

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 and Variable Importance for the Causal Effect of an Optimal Individualized Treatment Intervention

Simulating Supervised Learning Data

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

🌳 🎯 Cross Validated Decision Trees with Targeted Maximum Likelihood Estimation

Tools to Support Relative Importance Analysis

Build a predictive model for the sale prices of homes in a city and explore potential equity issues with the real-estate assessment process

Parkinson's Progression Marker Initiative data science challenge, 2016