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

Regression is one of the most powerful statistical tools for finding relationships in data. Python makes it easy, and it's much more flexible than a spreadsheet.

Learn to apply multiple regression techniques to predict continuous outcomes, use logistic regression for binary outcomes, and employ Cox regression for survival analysis.

Logistic regression with random effects is used to study the relationship between explanatory variables and a binary outcome in cases with nonindependent outcomes. In this paper, we examine in detail ...

Maximum likelihood estimation of the parameters of the binary logistic regression model for $\pr (H\mid x)$ is discussed with separate discussion of sampling from (i) the conditional distribution of H ...