Classification and regression trees are ideally suited for the analysis of complex ecological data. For such data, we require flexible and robust analytical methods, which can deal with nonlinear ...

The random forest model produces an ensemble of randomized decision trees, and is used for both classification and regression. The aggregated ensemble either combines the votes modally or averages ...

Regression and Classification Course This online data science course will explore concepts in statistical modeling, such as when to use certain models, how to tune those models, and determining ...

We evaluated four statistical models-Regression Tree Analysis (RTA), Bagging Trees (BT), Random Forests (RF), and Multivariate Adaptive Regression Splines (MARS)-for predictive vegetation mapping ...

DTSA 5020 Regression and Classification DTSA 5020 Regression and Classification Specialization: Intro to Statistical Learning Instructor: James Bird, Instructor Prior knowledge needed: Intro ...

PURPOSESystemic therapy with atezolizumab and bevacizumab can extend life for patients with advanced hepatocellular carcinoma (HCC). However, there is substantial variability in response to therapy ...

Consecutive patients with head and neck cancer (HNC) treated with curative-intent intensity-modulated radiation therapy (IMRT) (≥45 Gy) from 2011 to 2017 were included. Occurrence of ORN was ...