Logistic regression is a kind of supervised machine learning algorithm that is utilized to forecast a binary outcome and classify observations. Its dependent variable is a binary variable with two classes: 0 or 1. For example, it can be used to detect whether a loan applicant will default or not. It is a unique type of regression where the dependent or target variable is binary. It computes a log of the odds ratio of the target variable, which represents the probability of occurrence of an event, for example, the probability of a person suffering from diabetes.
Logistic regression is a kind of simple linear regression where the dependent or target variable is categorical. It uses the sigmoid function on the prediction result of linear regression. We can also use the logistic regression algorithm for multiple target classes. For multiple-class problems, it is called multinomial logistic regression. Multinomial logistic regression is a modification of logistic regression...
