Variable Importance Plots (VIPs)
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Updated
Oct 30, 2023 - R
Variable Importance Plots (VIPs)
Fast approximate Shapley values in R
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
Explainable Machine Learning in Survival Analysis
Automated Bidirectional Stepwise Selection On Python
Stability Selection with Error Control
Perform inference on algorithm-agnostic variable importance
Filter-based feature selection for mlr3
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
Perform inference on algorithm-agnostic variable importance in Python
Code for Variable Selection in Black Box Methods with RelATive cEntrality (RATE) Measures
📦 🎲 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
Tools to Support Relative Importance Analysis
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