New Developments in Unsupervised Outlier Detection Algorithms and Applications /

New Developments in Unsupervised Outlier Detection Algorithms and Applications /

書目詳細資料
Main Authors: Wang, Xiaochun (Author), Wang, Xiali (Author), Wilkes, Mitch (Author)
企業作者: SpringerLink (Online service)
總結:XXI, 277 p. 138 illus., 120 illus. in color.
text
語言:英语
出版: Singapore : Springer Nature Singapore : Imprint: Springer, 2021.
版:1st ed. 2021.
主題:
Computational intelligence.
Data mining.
Engineering > Data processing.
Computational Intelligence.
Data Mining and Knowledge Discovery.
Data Engineering.
在線閱讀:https://doi.org/10.1007/978-981-15-9519-6
格式: 電子 電子書
書本目錄:
  • Overview and Contributions
  • Developments in Unsupervised Outlier Detection Research
  • A Fast Distance-Based Outlier Detection Technique Using A Divisive Hierarchical Clustering Algorithm
  • A k-Nearest Neighbour Centroid Based Outlier Detection Method
  • A Minimum Spanning Tree Clustering Inspired Outlier Detection Technique
  • A k-Nearest Neighbour Spectral Clustering Based Outlier Detection Technique
  • Enhancing Outlier Detection by Filtering Out Core Points and Border Points
  • An Effective Boundary Point Detection Algorithm via k-Nearest Neighbours Based Centroid
  • A Nearest Neighbour Classifier Based Automated On-Line Novel Visual Percept Detection Method
  • Unsupervised Fraud Detection in Environmental Time Series Data. .

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