Logistic regression is a powerful statistical method that is used to model the probability that a set of explanatory (independent or predictor) variables predict data in an outcome (dependent or ...

Dr. James McCaffrey of Microsoft Research demonstrates applying the L-BFGS optimization algorithm to the ML logistic regression technique for binary classification -- predicting one of two possible ...

Logistic regression is often used instead of Cox regression to analyse genome-wide association studies (GWAS) of single-nucleotide polymorphisms (SNPs) and disease outcomes with cohort and case-cohort ...

Microsoft Research's Dr. James McCaffrey show how to perform binary classification with logistic regression using the Microsoft ML.NET code library. The goal of binary classification is to predict a ...

New insights into cancer are needed to help improving care and prevention. This requires broad and rich data, for instance to develop machine-learning models that can evaluate treatment outcomes.

Andriy Blokhin has 5+ years of professional experience in public accounting, personal investing, and as a senior auditor with Ernst & Young. Thomas J Catalano is a CFP and Registered Investment ...