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 ...

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

During the making of an AI model, Performance metrics like accuracy, precision, recall, F1-score, ROC curves are used to ...

Binary-response regression models in which the link function is a family defined by one or more unknown shape parameters are considered. Detailed attention is given to the two single-parameter ...

In terms of financial data, the most appropriate model would be a logistic regression, mostly because of the leptokurtic nature of the probability space associated with the logistic cumulative ...

The paper discusses some diagnostic tools for binary logistic regression which use smoothing techniques. Smoothed binary data are employed to devise a battery of diagnostic plots, from simple ...

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