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New Developments in Unsupervised Outlier Detection
Xiaochun Wang
Xiali Wang
Mitch Wilkes
其他書名
Algorithms and Applications
出版
Springer Nature
, 2020-11-24
主題
Technology & Engineering / Engineering (General)
Computers / Data Science / Data Analytics
Computers / Data Science / General
Computers / Artificial Intelligence / General
Technology & Engineering / General
Computers / Database Administration & Management
ISBN
9811595194
9789811595196
URL
http://books.google.com.hk/books?id=9zMLEAAAQBAJ&hl=&source=gbs_api
EBook
SAMPLE
註釋
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.