Ordinal regression and classification methods form a vital branch of statistical learning wherein the outcome variable possesses an inherent order. Unlike conventional classification problems ...

Ji Zhu, Trevor Hastie, Kernel Logistic Regression and the Import Vector Machine, Journal of Computational and Graphical Statistics, Vol. 14, No. 1 (Mar., 2005), pp. 185-205 ...

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 ...

We compared predictive abilities for two survival models (Cox proportional hazards and random survival forest) and four classification methods (logistic regression, support vector machines, random ...

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

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.