Encyclopedia of Machine Learning

The style of the entries in the Encyclopedia of Machine Learning is expository and tutorial, making the book a practical resource for machine learning experts, as well as professionals in other fields who need to access this vital information but may not have the time to work their way through an entire text on their topic of interest.

Abstract

Learning came to be identified as a research field in its own right as the workshops evolved into international conferences and journals of machine learning appeared.Although the field coalesced in the s, research on what we now call machine learning has a long history.In his  paper on "Computing Machinery and Intelligence", Alan Turing introduced his imitation game as a means of determining if a machine could be considered intelligent.In the same paper he speculates that programming the computer to have adult level intelligence would be too difficult."Instead of trying to produce a programme to simulate the adult mind, why not rather try to produce one which simulates the child's?If this were then subjected to an appropriate course of education one would obtain the adult brain".Investigations into induction, a fundamental operation in learning, go back much further to Francis Bacon and David Hume in the th and th centuries.Early approaches followed the classical AI tradition of symbolic representation and logical inference.As machine learning began to be used in a wide variety of areas, the range of techniques expanded to incorporate ideas from psychology, information theory, statistics, neuroscience, genetics, operations research and more.Because of this diversity, it is not always easy for a new researcher to find his or her way around the machine learning landscape.The purpose of this encyclopedia is to guide enquiries into the field as a whole and to serve as an entry point to specific topics, providing overviews and, most importantly, references to source material.All the entries have been written by experts in their field and have been refereed and revised by an international editorial board consisting of leading machine learning researchers.Putting together an encyclopedia for such a diverse field has been a major undertaking.We thank all the authors, without whom this would not have been possible.They have devoted their expertise and patience to the project because of their desire to contribute to this dynamic and still growing field.A project as large as this could only succeed with the help of the area editors whose specialised knowledge was essential in defining the range and structure of the entries.