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

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 whether other options will provide certain ...

Regularization methods are characterized by loss functions measuring data fits and penalty terms constraining model parameters. The commonly used quadratic loss is not suitable for classification with ...

Classification and regression tree (CART) methods are a class of data mining techniques which constitute an alternative approach to classical regression. CART methods are frequently used in ...

Motivated by the significant advances in integer optimization in the past decade, we introduce mixed-integer optimization methods to the classical statistical problems of classification and regression ...

Morbidity After Sentinel Lymph Node Biopsy in Primary Breast Cancer: Results From a Randomized Controlled Trial Data were uniformly collected on 1,433 referred men with a serum prostate-specific ...

Clinical Calculator for Predicting Freedom From Recurrence After Resection of Stage I-III Colon Cancer in Patients With Microsatellite Instability Systemic therapy with atezolizumab and bevacizumab ...

Dr. James McCaffrey of Microsoft Research uses a full code program, examples and graphics to explain multi-class logistic regression, an extension technique that allows you to predict a class that can ...