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.

The simplest form of regression in Python is, well, simple linear regression. With simple linear regression, you're trying to ...

In this article, an exact conditional goodness-of-fit test for the logistic regression model with grouped binomial response data is proposed. Two efficient algorithms are presented for carrying out ...

Course Topics"Logistic and Poisson Regression," Wednesday, November 5: The fourth LISA mini course focuses on appropriate model building for categorical response data, specifically binary and count ...

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 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 ...

Logistic regression was used to develop a risk prediction model using the FIT result and screening data: age, sex and previous screening history.

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