Outlier detection in complex categorical data by modeling the feature value couplings

Outlier detection in complex categorical data by modeling the feature value couplings

This paper introduces a novel unsupervised outlier detection method, namely Coupled Biased Random Walks (CBRW), for identifying outliers in categorical data with diversified frequency distributions and many noisy features. Existing pattern-based outlier detection methods are ineffective in handling...

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書目詳細資料
Main Authors:	PANG, Guansong, CAO, Longbing, CHEN, Ling
格式:	text
語言:	English
出版:	Institutional Knowledge at Singapore Management University 2016
主題:	Databases and Information Systems Data Storage Systems
在線閱讀:	https://ink.library.smu.edu.sg/sis_research/7146 https://ink.library.smu.edu.sg/context/sis_research/article/8149/viewcontent/272.pdf
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