Supervised Learning and Data Mining

Supervised learning from examples involves learning a function y = f(x) from training examples of the form (x, f(x)). A wide range of algorithms have been developed for this task including decision trees, neural networks, association rules, belief networks, and the nearest neighbor rule. Despite the mature state of this field, there are many important open problems. Many of these result from the recent interest in applying machine learning algorithms to analyze large amounts of corporate and scientific data--"data mining".