Presents the key algorithms and theory that form the core of machine learning. Discusses such theoretical issues as How does learning performance vary with the number of training examples presented? and Which learning algorithms are most appropriate for various types of learning tasks? DLC: Computer algorithms
Ch1. Introduction
Ch2. Concept Learning and the General-to-Specific Ordering
Ch3. Decision Tree Learning
Ch4. Artificial Neural Networks
Ch5. Evaluating Hypotheses
Ch6. Bayesian Learning
Ch7. Computational Learning Theory
Ch8. Instance-Based Learning
Ch9. Inductive Logic Programming
Ch10. Analytical Learning
Ch11. Combining Inductive and Analytical Learning
Ch12. Reinforcement Learning.