There are dozens of code libraries and tools that can create a logistic regression prediction model, including Keras, scikit-learn, Weka and PyTorch. When training a logistic regression model, there ...

Given logistic regression is substantially more computationally efficient than Cox regression in both settings, we propose a two-step approach to GWAS in cohort and case-cohort studies.

The term "logistic regression" encompasses logit modeling, probit modeling, and tobit modeling and the significance tests of their estimates. A total of 52 articles were identified as using logistic ...

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

With many nuisance parameters to eliminate and missing covariates, many investigators exclude any subject with missing covariates and then use conditional logistic regression, often called a ...

Classify: Weka trains and tests learning schemes that perform classification or regression. The classifiers can be divided into Bayesian, trees, rules, functions and lazy.

What are the advantages of logistic regression over decision trees? This question was originally answered on Quora by Claudia Perlich.