<Tr> <Td> <Ul> <Li> </Li> <Li> </Li> <Li> </Li> </Ul> </Td> </Tr> <Ul> <Li> </Li> <Li> </Li> <Li> </Li> </Ul> <P> Supervised learning is the machine learning task of learning a function that maps an input to an output based on example input - output pairs . It infers a function from labeled training data consisting of a set of training examples . In supervised learning, each example is a pair consisting of an input object (typically a vector) and a desired output value (also called the supervisory signal). A supervised learning algorithm analyzes the training data and produces an inferred function, which can be used for mapping new examples . An optimal scenario will allow for the algorithm to correctly determine the class labels for unseen instances . This requires the learning algorithm to generalize from the training data to unseen situations in a "reasonable" way (see inductive bias). </P> <P> The parallel task in human and animal psychology is often referred to as concept learning . </P>

Machine learning task of inferring a function from labelled training data is known as