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New Developments in Unsupervised Outlier Detection: Algorithms and Applications book cover by Xiaochun Wang, Xiali Wang, Mitch Wilkes
Hardcover

New Developments in Unsupervised Outlier Detection: Algorithms and Applications

by Xiaochun Wang, Xiali Wang and Mitch Wilkes

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Hardcover · 277 pages Springer Nature Singapore · 2020

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About the book

New Developments in Unsupervised Outlier Detection

This book enriches unsupervised outlier detection research by proposing several new distance-based and density-based outlier scores in a k-nearest neighbors’ setting. The respective chapters highlight the latest developments in k-nearest neighbor-based outlier detection research and cover such topics as our present understanding of unsupervised outlier detection in general; distance-based and density-based outlier detection in particular; and the applications of the latest findings to boundary point detection and novel object detection. The book also offers a new perspective on bridging the gap between k-nearest neighbor-based outlier detection and clustering-based outlier detection, laying the groundwork for future advances in unsupervised outlier detection research.

The authors hope the algorithms and applications proposed here will serve as valuable resources for outlier detection researchers for years to come.



Details

Publisher
Springer Nature Singapore
Authors
Xiaochun Wang, Xiali Wang, Mitch Wilkes
Format
Hardcover
Published
Nov 25, 2020
ISBN-13
9789811595189
Pages
277
Printing
Printed on demand
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