Ordinal regression and classification methods form a vital branch of statistical learning wherein the outcome variable possesses an inherent order. Unlike conventional classification problems ...

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

The covariance-regularized regression framework is extended to generalized linear models and linear discriminant analysis, and is used to analyse gene expression data sets with multiple class and ...

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 ...

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 ...

Basic logistic regression classification is arguably the most fundamental machine learning (ML) technique. Basic logistic regression can be used for binary classification, for example predicting if a ...

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 ...