Introduction to Multiclass Logistic Regression Classification

Logistic regression is one of the most popular and widely used classification algorithms, and by default, it’s limited to a binary class classification problem. However, logistic regression can be used for multiclass classification using extensions like one-vs-rest (OVR) and multinomial.

• In OVR, the problem is first transformed into multiple binary classification problems, and under the hood, separate binary classifiers are trained for all classes.

• In multinomial, the solvers learn an accurate multinomial logistic regression model. In this case, the probability estimates should be better calibrated than OVR. The cross-entropy error/loss function supports ...