About this book
Introduction
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.
Keywords
algorithms case-based reasoning classification cognition data mining learning machine learning
Editors and affiliations
Bibliographic information
- DOI https://doi.org/10.1007/978-94-017-2053-3
- Copyright Information Springer Science+Business Media B.V. 1997
- Publisher Name Springer, Dordrecht
- eBook Packages Springer Book Archive
- Print ISBN 978-90-481-4860-8
- Online ISBN 978-94-017-2053-3
- About this book