An instance of supervised learning that identifies the category or categories which a new instance of dataset belongs.

In machine learning and statistics, classification refers to the problem of predicting category memberships based on a set of pre-labeled examples. It is thus a type of supervised learning.

Some of the most important classification algorithms are support vector machines , logistic regression, naive Bayes, random forest and artificial neural networks .

When we wish to associate inputs with continuous values in a supervised framework, the problem is instead known as . The unsupervised counterpart to classification is known as (or cluster analysis), and involves grouping data into categories based on some measure of inherent similarity.