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 ...

A boosted regression tree model showed that maximum tree height was correlated with water availability (24%), followed by soil properties including total P (11%), Mg (10%) and total N (9%), amongst ...

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 ...