 |
GetTextbooks.com
Compare Prices & Save up to 90% |
|
|
|
| Login | Sign up | My Wish List |
 | | Lazy Learning by David W. Aha (Editor) ISBN-10: 9780792345848 ISBN-10: 0-7923-4584-3 ISBN-13: 9780792345848 ISBN-13: 978-0-7923-4584-8 Hardcover 1997-05-31 Springer Find Lowest Price |
Editorials | ||
Product Description This edited collection describes recent progress on lazy learning, a branch of machine learning concerning algorithms that defer the processing of their inputs, reply to information requests by combining stored data, and typically discard constructed replies. It is the first edited volume in AI on this topic, whose many synonyms include `instance-based', `memory-based'. `exemplar-based', and `local learning', and whose topic intersects case-based reasoning and edited k-nearest neighbor classifiers. It is intended for AI researchers and students interested in pursuing recent progress in this branch of machine learning, but, due to the breadth of its contributions, it should also interest researchers and practitioners of data mining, case-based reasoning, statistics, and pattern recognition. | ||
Reviews | ||
Relevant, Current Contribution on Important Subject This book covers "local" machine learning methods (k-NN, local regression, etc.) as a collection of distinct contributions. The material is current and useful. Two drawbacks that kept me from giving 5 stars: too little comparison to alternative techniques (nerual networks, parametric regression, tree induction, etc.) and the lack of an index. | ||