Machine learning systems use tree-based models both for classification and regression problems. Mathias said that HHS has also started using new AI technology to speed up counterfeit drug detection at ...

Researchers have developed advanced, non-destructive models to measure the aboveground biomass and volume of Populus ...

Other tree ensemble regression techniques include random forest regression (and a variant called bagging regression), and gradient boosting regression. Compared to other regression techniques, ...

Random forest regression is an integrated learning method that combines multiple decision tree models into a more powerful model that can effectively avoid overfitting problems and can handle ...

The identification of risk-based groups through tree-based models will inform clinical practice guidelines about having risk-based follow-up care. Relevance (S. Halabi) This study presents a SDT model ...

Linear regression models were developed for four ecologically and economically important tree species of Meghalaya, India, viz. Betula alnoides, Duabanga grandiflora, Magnolia champaca and Toona ...