In Machine Learning, for how many classes can Logistic Regression be used?

Shriyansh

I have basic knowledge of Logistic Regression in ML. Can you properly explain how many classes can Logistic Regression be used?

priyankaraul

In machine learning, logistic regression is a commonly used algorithm for classification problems. Logistic regression can be used to classify data into two classes, known as binary classification. However, it can also be used to classify data into multiple classes, known as multi-class classification. This is done through a technique known as one-vs-all or one-vs-rest, where logistic regression is applied to each class separately by treating it as a binary classification problem. The class with the highest probability of being the correct class based on the logistic regression is then chosen as the predicted class. In this way, logistic regression can be used for multi-class classification problems with any number of classes.