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 ...

As the coronavirus disease 2019 (COVID-19) pandemic has spread across the world, vast amounts of bioinformatics data have been created and analyzed, and logistic regression models have been key to ...

The fundamental technique has been studied for decades, thus creating a huge amount of information and alternate variations that make it hard to tell what is key vs. non-essential information.

Understanding the mechanics of adaptive evolution requires not only knowing the quantitative genetic bases of the traits of interest but also obtaining accurate measures of the strengths and modes of ...

Results from classic linear regression regarding the effect of adjusting for covariates upon the precision of an estimator of exposure effect are often assumed to apply more generally to other types ...

Multicenter Phase I/II Study of Cetuximab With Paclitaxel and Carboplatin in Untreated Patients With Stage IV Non–Small-Cell Lung Cancer Data from 1,066 patients recruited from nine European centers ...