Finding Groups in Data

In this chapter, classification methods will be discussed, which have been extensively implemented for analysing big data in various fields such as customer segmentation, fraud detection, computer vision, speech recognition and medical diagnosis. In brief, classification can be viewed as a labelling process for new observations, aiming at determining to which of a set of categories an unlabelled object should belong. Fundamentals of classification will be introduced first, followed by a discussion on several classification methods that have been popular in big data applications, including the k -nearest neighbour algorithm, regression models, Bayesian networks, artificial neural networks and decision trees. Examples will be provided to demonstrate the implementation of these methods.