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Found 3 papers, 3 papers with code
GP-BART: a novel Bayesian additive regression trees approach using Gaussian processes
The Bayesian additive regression trees (BART) model is an ensemble method extensively and successfully used in regression tasks due to its consistently strong predictive performance and its ability to quantify uncertainty.
Random Machines Regression Approach: an ensemble support vector regression model with free kernel choice
Machine learning techniques always aim to reduce the generalized prediction error.
Random Machines: A bagged-weighted support vector model with free kernel choice
Improvement of statistical learning models in order to increase efficiency in solving classification or regression problems is still a goal pursued by the scientific community.
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