Power Search
Low Price Guarantee
We Take School POs
Lazy Learning Reprinted from Edition
Contributor(s): AHA, David W. (Editor)

View larger image

 ISBN: 0792345843     ISBN-13: 9780792345848
Publisher: Springer
OUR PRICE: $161.49  

Binding Type: Hardcover - See All Available Formats & Editions
Published: May 1997
Qty:

Annotation: 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.
Additional Information
BISAC Categories:
- Computers | Intelligence (ai) & Semantics
Dewey: 006.31
LCCN: 97016416
Physical Information: 0.94" H x 6.14" W x 9.21" L (1.71 lbs) 424 pages
Features: Bibliography, Illustrated
 
Descriptions, Reviews, Etc.
Publisher 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.
 
Customer ReviewsSubmit your own review
 
To tell a friend about this book, you must Sign In First!