In recent columns we showed how linear regression can be used to predict a continuous dependent variable given other independent variables 1,2. When the dependent variable is categorical, a common ...

Dr. James McCaffrey of Microsoft Research uses code samples, a full C# program and screenshots to detail the ins and outs of kernal logistic regression, a machine learning technique that extends ...

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 ...

Logistic regression is a powerful technique for fitting models to data with a binary response variable, but the models are difficult to interpret if collinearity, nonlinearity, or interactions are ...

Logistic regression has found wide acceptance as a model for the dependence of a binary response variable on a vector of explanatory variables. It can also be used, however, as a maximization ...

Northampton, MA. OriginLab, a publisher of data-analysis and graphing software, today announced the release of Origin and OriginPro 2017. These latest versions of OriginLab’s software applications add ...