Variable Importance Plots (VIPs)
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Updated
Oct 30, 2023 - R
Variable Importance Plots (VIPs)
Fast approximate Shapley values in R
🎯🎓 Generalized Targeted Learning Framework
SurvSHAP(t): Time-dependent explanations of machine learning survival models
Variable importance through targeted causal inference, with Alan Hubbard
Routines and data structures for using isarn-sketches idiomatically in Apache Spark
Explainable Machine Learning in Survival Analysis
Stability Selection with Error Control
Automated Bidirectional Stepwise Selection On Python
Filter-based feature selection for mlr3
Perform inference on algorithm-agnostic variable importance
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…
Simulating Supervised Learning Data
Code for the paper 'Variable Selection with Copula Entropy' published on Chinese Journal of Applied Probability and Statistics
Code for Variable Selection in Black Box Methods with RelATive cEntrality (RATE) Measures
Perform inference on algorithm-agnostic variable importance in Python
📦 🎲 R/txshift: Efficient Estimation of the Causal Effects of Stochastic Interventions, with Corrections for Outcome-Dependent Sampling
🎯 💯 Targeted Learning and Variable Importance for the Causal Effect of an Optimal Individualized Treatment Intervention
Variable importance via oscillations
Tools to Support Relative Importance Analysis
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