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

Example 29.1: Logistic Regression In an experiment comparing the effects of five different drugs, each drug is tested on a number of different subjects. The outcome of each experiment is the presence ...

Logistic Regression is a widely used model in Machine Learning. It is used in binary classification, where output variable can only take binary values. Some real world examples where Logistic ...

Given logistic regression is substantially more computationally efficient than Cox regression in both settings, we propose a two-step approach to GWAS in cohort and case-cohort studies.

Example 39.1: Stepwise Logistic Regression and Predicted Values Consider a study on cancer remission (Lee 1974). The data, consisting of patient characteristics and whether or not cancer remission ...

Standard chi-squared, X2, or likelihood ratio, G2, test statistics for logistic regression analysis, involving a binary response variable, are adjusted to take account of the survey design. These ...

Laurence D. Robinson, Nicholas P. Jewell, Some Surprising Results about Covariate Adjustment in Logistic Regression Models, International Statistical Review / Revue Internationale de Statistique, Vol.

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