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

Logistic regression enables you to investigate the relationship between a categorical outcome and a set of explanatory variables. The outcome, or response, can be dichotomous (yes, no) or ordinal (low ...

Regression can be used on categorical responses to estimate probabilities and to classify.

The LOGISTIC and PROBIT procedures can perform logistic and ordinal logistic regression. See Chapter 5, "Introduction to Categorical Data Analysis Procedures," Chapter 39, "The LOGISTIC Procedure," ...

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 ...

Bayesian analyses of multivariate binary or categorical outcomes typically rely on probit or mixed effects logistic regression models that do not have a marginal logistic structure for the individual ...