Mining of Outlier Detection in Large Categorical Datasets

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Provided by: Creative Commons
Topic: Big Data
Format: PDF
Outlier detection will typically be thought of as a pre-processing step for locating, throughout a data set, those objects that do not fits well-defined notions of expected behavior. It is vital in process for locating novel or isolated events, anomalies, vicious actions, exceptional phenomena, etc. The authors have got an inclination to reinvestigating outlier detection for categorical data sets. This drawback is very hard owing to the matter of shaping a pregnant similarity live for categorical data.
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