There are many other techniques for binary classification, but logistic regression was one of the earliest developed and the technique is considered a fundamental machine learning skill for data ...

Dr. James McCaffrey of Microsoft Research uses code samples, a full C# program and screenshots to detail the ins and outs of kernal logistic regression, a machine learning technique that extends ...

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

Multivariate adaptive regression splines (MARS) have useful features to effectively reduce the number of terms in a model.

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," ...

Some results are presented on improving the fit of the logistic regression model for binary data by transforming the vector of explanatory variables. The methods are based on consideration of the ...

We consider the case-control problem with stratified samples and assume a logistic model that does not include terms for strata, i.e., for fixed covariates the (prospective) probability of disease ...