This book is an attempt to present and discuss such issues and principles (common to all methods) and then describe representative popular methods originating from statistics, neural networks, and pattern recognition. Often methods developed in different fields can be related to a common conceptual framework. This approach enables better understanding of a method’s properties, and it has methodological advantages over traditional ‘‘cookbook’’ descriptions of various learning algorithms.