Multi-class logistic regression is an extension technique that allows you to predict a class that can be one of three or more possible values. An example of multi-class classification is predicting ...

For example, if most of the data items are class moderate (say, 900 out of 1,000) and only a few are class conservative (say, 40 out of 1,000) and class liberal (60 out of 1,000), then a model that ...

Often when you start learning about classification problems in Machine Learning, you start with binary classification or where there are only two possible outcomes, such as spam or not spam, fraud or ...

The Data Science Lab. Multi-Class Classification Using PyTorch: Defining a Network. Dr. James McCaffrey of Microsoft Research explains how to define a network in installment No. 2 of his four-part ...

Zero, one or multiple labels can be associated with an instance(or example). It is more general than multi-class. classification where one and only one label assigned to an example. You can think the ...

Multi-class classification: We are categorizing emails into six distinct classes. Multinomial Naïve Bayes supports multi-class classification out of the box, making it a clean fit for this problem.

The goal of a multi-class classification problem is to predict a value that can be one of three or more possible discrete values, for example "low," "medium" or "high" for a person's annual income.