What is the primary function of a classifier in machine learning?

The primary function of a classifier in machine learning is to predict the category or class of data inputs. Classifiers are designed to take input features and assign them to predefined classes based on learned patterns from training data. Through the process of training, a classifier learns to distinguish between different categories by identifying features that are indicative of each class.

For instance, in a spam detection system, the classifier learns from a dataset of emails that are labeled as either 'spam' or 'not spam.' Once trained, when a new email comes in, the classifier analyzes its features—such as the presence of certain words or the layout—and predicts which category it belongs to.

The role of a classifier is distinctly focused on categorization, which aligns with supervised learning approaches where the goal is to assign new instances to one of the predefined classes based on the training it has received.