From aa3028df0ec54d41b67e2b9911f94bcf402b3732 Mon Sep 17 00:00:00 2001 From: Drew Herren Date: Wed, 17 Dec 2025 13:25:54 -0600 Subject: [PATCH] Updated stochtree references --- MachineLearning.md | 9 ++++----- 1 file changed, 4 insertions(+), 5 deletions(-) diff --git a/MachineLearning.md b/MachineLearning.md index 9184ea4..bc0f390 100644 --- a/MachineLearning.md +++ b/MachineLearning.md @@ -104,9 +104,7 @@ roughly structured into the following topics: `r pkg("trtf")` (predictive transformation forests, possibly under censoring and truncation) and `r pkg("grf")` (an implementation of generalised random - forests). Bayesian Additive Regression Trees (BART) and Bayesian Causal - Forests (BCF) are implemented in `r pkg("stochtree")`. Random ferns for - classification are implemented in `r pkg("rFerns")`. + forests). Random ferns for classification are implemented in `r pkg("rFerns")`. - *Regularized and Shrinkage Methods* : Regression models with some constraint on the parameter estimates can be fitted with the @@ -183,8 +181,8 @@ roughly structured into the following topics: - *Bayesian Methods* : Bayesian Additive Regression Trees (BART), where the final model is defined in terms of the sum over many weak learners (not unlike ensemble methods), are implemented in packages - `r pkg("BayesTree")`, `r pkg("BART")`, and - `r pkg("bartMachine")`. Bayesian nonstationary, + `r pkg("BayesTree")`, `r pkg("BART")`, `r pkg("bartMachine")`, + and `r pkg("stochtree")`. Bayesian nonstationary, semiparametric nonlinear regression and design by treed Gaussian processes including Bayesian CART and treed linear models are made available by package `r pkg("tgp")`. Bayesian structure @@ -241,6 +239,7 @@ roughly structured into the following topics: models. Building upon the `r pkg("mlr3")` ecosystem, estimation of causal effects can be based on an extensive collection of machine learning methods. + Bayesian Causal Forests (BCF) are implemented in `r pkg("stochtree")`. - *Other procedures* : Evidential classifiers quantify the uncertainty about the class of a test pattern using a Dempster-Shafer mass function in package `r pkg("evclass")`. The