New Developments in Unsupervised Outlier Detection: Algorithms and Applications
New Developments in Unsupervised Outlier Detection: Algorithms and Applications by Xiaochun Wang
English | PDF | 2021 | 287 Pages | ISBN : 9811595186 | 9.6 MB
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.
Please Please :( We Are Here For You And Without You And Your Support We Can’t Continue
Thanks For Buying Premium From My Links For Support
Thanks For Buying Premium From My Links For Support
i will be very grateful when you support me and buy Or Renew Your Premium from my Blog links
i appreciate your support Too much as it will help me to post more and more
Without You And Your Support We Can’t Continue
Thanks For Buying Premium From My Links For Support
i appreciate your support Too much as it will help me to post more and more
Without You And Your Support We Can’t Continue
Thanks For Buying Premium From My Links For Support