Logistic regression is a common Machine Learning method that belongs to the Supervised Learning technique. It is used to forecast the categorical dependent variable from a group of independent variables. A categorical dependent variable's output is predicted using logistic regression.
A logistic regression, for example, could be used to forecast whether a political candidate will win or lose an election, or if a high school student would be admitted or not to a specific college. These binary outcomes allow for simple choices between two options.
The link function is log(p/1-p). We can model a non-linear link in a linear way by applying a logarithmic transformation to the outcome variable. After substituting y's value, we get: This is the Logistic Regression equation. The odd ratio here is (p/1-p).