ABSTRACT
Classification is a method of supervised learning in which an algorithm is trained to assign one or more predefined labels to a given input. The goal of classification is to learn a function that can accurately predict the class label of an unseen input, based on the class labels of a set of labeled training data. Classification algorithms typically take as input a set of feature values for a given input and use these features to predict the class label. Common examples of classification problems include image recognition, spam detection, and natural language processing.
