In machine learning

Machine learning

Machine learning, a branch of artificial intelligence, is a scientific discipline concerned with the design and development of algorithms that allow computers to evolve behaviors based on empirical data, such as from sensor data or databases...

, multiclass or multinomial classification is the problem of classifying instances into more than two classes.

While some classification algorithms naturally permit the use of more than two classes, others are by nature binary algorithms; these can, however, be turned into multinomial classifiers by a variety of strategies. Among these strategies are the one-vs.-all (or one-vs.-rest, OvA or OvR) strategy, where a single classifier is trained per class to distinguish that class from all other classes. Prediction is then performed by predicting using each binary classifier, and choosing the prediction with the highest confidence score (e.g., the highest probability of a classifier such as Naive Bayes

Naive Bayes classifier

A naive Bayes classifier is a simple probabilistic classifier based on applying Bayes' theorem with strong independence assumptions...

).

Multiclass classification should not be confused with multi-label classification

Multi-label classification

In machine learning, multi-label classification is a variant of the classification problem where multiple target labels must be assigned to each instance...

, where multiple classes are to be predicted for each problem instance.