Supervised Learning: Classification

Supervised learning is the task of building a model that is able to fit the available observations. In the area of supervised learning, classification is one of the most studied problems. Given a set of predefined class labels (two or more) and a set of available observations, the aim is to build a model based on the features of the observations that is able to assign each observation to the corresponding class. In Bioinformatics several problems can be formulated as a classification task. This article introduces several supervised learning techniques that are commonly used to address a classification problem, presenting the most used measures to evaluate the performance of a classification model.