Lazy Learning
Author | : David W. Aha |
Publisher | : Springer Science & Business Media |
Total Pages | : 421 |
Release | : 2013-06-29 |
ISBN-10 | : 9789401720533 |
ISBN-13 | : 9401720533 |
Rating | : 4/5 (533 Downloads) |
Download or read book Lazy Learning written by David W. Aha and published by Springer Science & Business Media. This book was released on 2013-06-29 with total page 421 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.