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Efficient and effective outlier detection.

by Chiu Lai Mei. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2003. / Includes bibliographical references (leaves 142-149). / Abstracts in English and Chinese. / Abstract --- p.ii / Acknowledgement --- p.vi / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Outlier Analysis --- p.2 / Chapter 1.2 --- Problem Statement --- p.4 / Chapter 1.2.1 --- Binary Property of Outlier --- p.4 / Chapter 1.2.2 --- Overlapping Clusters with Different Densities --- p.4 / Chapter 1.2.3 --- Large Datasets --- p.5 / Chapter 1.2.4 --- High Dimensional Datasets --- p.6 / Chapter 1.3 --- Contributions --- p.8 / Chapter 2 --- Related Work in Outlier Detection --- p.10 / Chapter 2.1 --- Outlier Detection --- p.11 / Chapter 2.1.1 --- Clustering-Based Methods --- p.11 / Chapter 2.1.2 --- Distance-Based Methods --- p.14 / Chapter 2.1.3 --- Density-Based Methods --- p.18 / Chapter 2.1.4 --- Deviation-Based Methods --- p.22 / Chapter 2.2 --- Breakthrough Outlier Notion: Degree of Outlier-ness --- p.25 / Chapter 2.2.1 --- LOF: Local Outlier Factor --- p.26 / Chapter 2.2.2 --- Definitions --- p.26 / Chapter 2.2.3 --- Properties --- p.29 / Chapter 2.2.4 --- Algorithm --- p.30 / Chapter 2.2.5 --- Time Complexity --- p.31 / Chapter 2.2.6 --- LOF of High Dimensional Data --- p.31 / Chapter 3 --- LOF': Formula with Intuitive Meaning --- p.33 / Chapter 3.1 --- Definition of LOF' --- p.33 / Chapter 3.2 --- Properties --- p.34 / Chapter 3.3 --- Time Complexity --- p.37 / Chapter 4 --- "LOF"" for Detecting Small Groups of Outliers" --- p.39 / Chapter 4.1 --- "Definition of LOF"" " --- p.40 / Chapter 4.2 --- Properties --- p.41 / Chapter 4.3 --- Time Complexity --- p.44 / Chapter 5 --- GridLOF for Pruning Reasonable Portions from Datasets --- p.46 / Chapter 5.1 --- GridLOF Algorithm --- p.47 / Chapter 5.2 --- Determine Values of Input Parameters --- p.51 / Chapter 5.2.1 --- Number of Intervals w --- p.51 / Chapter 5.2.2 --- Threshold Value σ --- p.52 / Chapter 5.3 --- Advantages --- p.53 / Chapter 5.4 --- Time Complexity --- p.55 / Chapter 6 --- SOF: Efficient Outlier Detection for High Dimensional Data --- p.57 / Chapter 6.1 --- Motivation --- p.57 / Chapter 6.2 --- Notations and Definitions --- p.59 / Chapter 6.3 --- SOF: Subspace Outlier Factor --- p.62 / Chapter 6.3.1 --- Formal Definition of SOF --- p.62 / Chapter 6.3.2 --- Properties of SOF --- p.67 / Chapter 6.4 --- SOF-Algorithm: the Overall Framework --- p.73 / Chapter 6.5 --- Identify Associated Subspaces of Clusters in SOF-Algorithm . . --- p.74 / Chapter 6.5.1 --- Technical Details in Phase I --- p.76 / Chapter 6.6 --- Technical Details in Phase II and Phase III --- p.88 / Chapter 6.6.1 --- Identify Outliers --- p.88 / Chapter 6.6.2 --- Subspace Quantization --- p.90 / Chapter 6.6.3 --- X-Tree Index Structure --- p.91 / Chapter 6.6.4 --- Compute GSOF and SOF --- p.95 / Chapter 6.6.5 --- Assign SO Values --- p.95 / Chapter 6.6.6 --- Multi-threads Programming --- p.96 / Chapter 6.7 --- Time Complexity --- p.97 / Chapter 6.8 --- Strength of SOF-Algorithm --- p.99 / Chapter 7 --- "Experiments on LOF' ,LOF"" and GridLOF" --- p.102 / Chapter 7.1 --- Datasets Used --- p.103 / Chapter 7.2 --- LOF' --- p.103 / Chapter 7.3 --- "LOF"" " --- p.109 / Chapter 7.4 --- GridLOF --- p.114 / Chapter 8 --- Empirical Results of SOF --- p.121 / Chapter 8.1 --- Synthetic Data Generation --- p.121 / Chapter 8.2 --- Experimental Setup --- p.124 / Chapter 8.3 --- Performance Measure --- p.124 / Chapter 8.3.1 --- Quality Measurement --- p.127 / Chapter 8.3.2 --- Scalability of SOF-Algorithm --- p.136 / Chapter 8.3.3 --- Effect of Parameters on SOF-Algorithm --- p.139 / Chapter 9 --- Conclusion --- p.140 / Bibliography --- p.142 / Publication --- p.149

Identiferoai:union.ndltd.org:cuhk.edu.hk/oai:cuhk-dr:cuhk_324318
Date January 2003
ContributorsChiu, Lai Mei., Chinese University of Hong Kong Graduate School. Division of Computer Science and Engineering.
Source SetsThe Chinese University of Hong Kong
LanguageEnglish, Chinese
Detected LanguageEnglish
TypeText, bibliography
Formatprint, xiii, 149 leaves : ill. ; 30 cm.
RightsUse of this resource is governed by the terms and conditions of the Creative Commons “Attribution-NonCommercial-NoDerivatives 4.0 International” License (http://creativecommons.org/licenses/by-nc-nd/4.0/)

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