Data Mining: Concepts and Techniques, 3rd Edition

Publisher Summary

This chapter discusses the advanced techniques for data classification starting with Bayesian belief networks, which do not assume class conditional independence. Bayesian belief networks allow class conditional independencies to be defined between subsets of variables. They provide a graphical model of causal relationships, on which learning can be performed. Trained Bayesian belief networks can be used for classification. Backpropagation is a neural network algorithm for classification that employs a method of gradient descent. It searches for a set of weights that can model the data so as to minimize the mean-squared distance between the network’s class prediction and the actual class label of data tuples. Rules may be extracted ...