DirichletForest

This repository contains an implementation of a Dirichlet Random Forest, designed for modeling compositional (Dirichlet-distributed) data.

⚠️ Note: This project is still in progress. For a parallel version, see my DirichletRandomParallel repository.

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📦 Installation

Clone this repository and install locally in R:

devtools::install_github("https://github.com/Xaleed/DirichletForest.git")
 
library(DirichletForest)

# Generate predictors
n <- 500
p <- 4
X <- matrix(rnorm(n * p), n, p)

# Generate Dirichlet responses
if (!requireNamespace("MCMCpack", quietly = TRUE)) {
  install.packages("MCMCpack")
}
alpha <- c(2, 3, 4)
Y <- MCMCpack::rdirichlet(n, alpha)

# Fit a distributed Dirichlet Forest with 50 trees using 3 cores
df_par3 <- dirichlet_forest(X, Y, B = 50)

# Predict on new data (here we reuse X for illustration)
pred3 <- predict_dirichlet_forest(df_par3, X)