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.

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, ...

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 ...

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 ...