The study tested four machine learning algorithms to analyze the data: Gradient tree boosting, random forest, classification and regression trees, or CART, and support vector machine.

There are many machine learning techniques for multi-class classification. One of the most powerful techniques is to use the LightGBM (lightweight gradient boosting machine) system. LightGBM is a ...

Zurqani’s team ran four AI algorithms to crunch the data: Gradient Tree Boosting, Random Forest, CART (Classification and Regression Trees), and Support Vector Machine. The clear frontrunner was ...

Diagnoses, treatments, biochemical data, and histopathologic results were used to train predictive models of 30-day mortality using logistic regression with elastic net penalty, random forest, ...