Logistic regression is a statistical method used to examine the relationship between a binary outcome variable and one or more explanatory variables. It is a special case of a regression model that ...

A new study investigated how logistic regression model training affects performance, and which features are best to include when examining datasets from individuals suffering from COVID-19.

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 ...

Purpose To collect data for the development of a more universally useful logistic regression model to distinguish between a malignant and benign adnexal tumor before surgery. Patients and Methods ...

Although Cox and logistic regression models have been compared previously in cohort studies, this work does not completely cover the GWAS setting nor extend to the case-cohort study design.

Learn what is Logistic Regression Cost Function in Machine Learning and the interpretation behind it. Logistic Regression Cost function is "error" representation of the model. It shows how the ...

Logistic regression analysis of high-dimensional data, such as natural language text, poses computational and statistical challenges. Maximum likelihood estimation often fails in these applications.