I predict you'll find this logistic regression example with R to be helpful for gleaning useful information from common binary classification problems.

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 ...

The course will end with a brief introduction to regression involving binary response variables (Yes/No or 0/1 outcomes) using logistic regression and count response variables (whole numbers) using ...

Logistic regression is a widely applied tool for the analysis of binary response variables. Several test statistics have been proposed for the purpose of assessing the goodness of fit of the logistic ...

Motivated by these problems, we propose a new type of multivariate logistic distribution that can be used to construct a likelihood for multivariate logistic regression analysis of binary and ...

The models used are binary logistic regression models based on the full sample of U.S. adults surveyed for this study. The analyses are based on the weighted sample, thus adjusting for differences in ...

Binomial (or binary) logistic regression analysis is useful for predicting the presence or absence of a characteristic or outcome based on values of a set of predictor variables, and is applicable ...

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.