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bartMachine: Machine Learning with Bayesian Additive Regression Trees

arXiv 1312.2171 ↗First posted 8 Dec 2013stat.ML cs.LGcited by 24

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Abstract (arXiv)

We present a new package in R implementing Bayesian additive regression trees (BART). The package introduces many new features for data analysis using BART such as variable selection, interaction detection, model diagnostic plots, incorporation of missing data and the ability to save trees for future prediction. It is significantly faster than the current R implementation, parallelized, and capable of handling both large sample sizes and high-dimensional data.

Key facts. Cited by 24 papers in the map (data through 7 Oct 2026). First posted on arXiv 8 Dec 2013.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 5; 2022: 4; 2023: 3; 2024: 2; 2025: 6; 2026: 4.

24 papers.

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  1. 2022Generalized Bayesian Additive Regression Trees Models: Beyond Conditional Conjugacycited by 8
  2. 2022GP-BART: a novel Bayesian additive regression trees approach using Gaussian processescited by 7
  3. 2023Sharded Bayesian Additive Regression Treescited by 5
  4. 2021Adaptive network reliability analysis: Methodology and applications to power gridcited by 3
  5. 2021Accounting for shared covariates in semi-parametric Bayesian additive regression treescited by 2
  6. 2023Bayesian CART models for insurance claims frequencycited by 2
  7. 2024Very fast Bayesian Additive Regression Trees on GPUcited by 2
  8. 2025BARK: A Fully Bayesian Tree Kernel for Black-box Optimizationcited by 2
  9. 2021Uncovering Dominant Features in Short-term Power Load Forecasting Based on Multi-source Featurecited by 1
  10. 2022SoftBart: Soft Bayesian Additive Regression Treescited by 1
  11. 2025Horseshoe Forests for High-Dimensional Causal Survival Analysiscited by 1
  12. 2025Two-sample comparison through additive tree models for density ratioscited by 1
12 more
  1. 2021Machine learning in the social and health sciencescited by 0
  2. 2021A pragmatic approach to estimating average treatment effects from EHR data: the effect of prone positioning on mechanically ventilated COVID-19 patientscited by 0
  3. 2022Extraction of Visual Information to Predict Crowdfunding Successcited by 0
  4. 2023Co-data Learning for Bayesian Additive Regression Treescited by 0
  5. 2024What is to be gained by ensemble models in analysis of spectroscopic data?cited by 0
  6. 2025Functional BART with Shape Priors: A Bayesian Tree Approach to Constrained Functional Regressioncited by 0
  7. 2025Bayesian Hybrid Machine Learning of Gallstone Riskcited by 0
  8. 2025Bayesian Neural Networks for Functional ANOVA modelcited by 0
  9. 2026Bayesian Additive Distribution Regressioncited by 0
  10. 2026Improving the Efficiency of Subgroup Analysis in Randomized Controlled Trials with TMLEcited by 0
  11. 2026Semi-Parametric Bayesian Additive Regression Trees for Risk Prediction with High-Dimensional Epigenetic Signatures and Low-Dimensional Covariatescited by 0
  12. 2026Bayesian fusion forests for heterogeneous treatment effects on survival from randomised and real-world datacited by 0