New Developments in Unsupervised Outlier Detection: Algorithms and Applications

By Mitch Wilkes, Xiaochun Wang, Mitch Wilkes

Book Overview

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.

• Format: Hardcover
• Language: English
• ISBN: 9811595186
• ISBN13: 9789811595189
• Release Date: November 2020
• Publisher: Springer
• Length: 277 Pages
• Weight: 1.31 lbs.
• Dimensions: 0.7" x 6.1" x 9.2"