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 ...

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 ...

Boosted regression tree analysis was used to determine any consistent patterns between physical variables and benthic algal cover. Generally, air temperature and the Southern Oscillation Index (SOI) ...

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 ...

Researchers have developed a hybrid machine learning model combining Gradient Boosting Regression Trees with Bayesian Optimization to accurately predict the compressive strength of self-compacting ...