The data doctor continues his exploration of Python-based machine learning techniques, explaining binary classification using logistic regression, which he likes for its simplicity. The goal of a ...

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 ...

In this episode of eSpeaks, Jennifer Margles, Director of Product Management at BMC Software, discusses the transition from traditional job scheduling to the era of the autonomous enterprise. eSpeaks’ ...

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 ...

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.

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 ...