They then extended their analysis to include tree-based ML models (random forest and gradient-boosted regression trees) and neural networks. LASSO works well when there is a mix of strong and weak ...

A new study in PNAS Nexus introduces a predictive framework that uses mosquito surveillance data, weather, and land cover to ...

In this paper, we discuss how tree-based machine learning techniques can be used in the context of derivatives pricing. Gradient boosted regression trees are employed to learn the pricing map for a ...

Decision tree regression is a fundamental technique that can be used by itself, and is also the basis for powerful ensemble techniques (a collection of many decision trees), notably, AdaBoost ...

Here we use boosted regression tree analyses to test the relative importance of multiple biophysical drivers on coral and macroalgal cover using a long-term (12–18 yr) data set collected from reefs at ...

The developed model uses regression trees as the base learner, and is generally applicable to varying-coefficient models with a large number of mixed-type varying-coefficient variables, which proves ...