bartrs 0.2.0

Rust implementation of Bayesian Additive Regression Trees for Probabilistic programming with PyMC

PyMC-BART-rs

High-performance Rust implementation of PyMC-BART. This implementation provides an optimized Particle Gibbs BART (PGBART) sampler designed for performance and extensibility.

Table of Contents

• Installation
• Usage
• Modifications

Installation

PyMC-BART is available on PyPI with pre-built wheels for Linux (x86_64, aarch64), Windows (x64), and macOS (x86_64, aarch64). To install using pip

pip install pymc-bart-rs

Usage

Get started by using PyMC-BART to set up a BART model

import pymc as pm
import pymc_bartrs as pmb

X, y = ... # Your data replaces "..."
with pm.Model() as model:
    bart = pmb.BART('bart', X, y)
    ...
    idata = pm.sample()