Weighted Outlier Detection of High-Dimensional Categorical Data Using Feature Grouping
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DOI: 10.1109/tsmc.2018.2847625
Abstract: We propose a weighted outlier mining method called WATCH to identify outliers in high-dimensional categorical datasets. WATCH is composed of two distinctive modules: 1) feature grouping by the virtue of correlation measurement among features and… read more here.
Keywords: weighted outlier; outlier mining; dimensional categorical; high dimensional ... See more keywords