DensityBasedOutlierDetection

ShubhaShubha MemberPosts:139Guru
edited November 2018 inHelp
Hi,

I am a bit confused with the definitions given for "DensityBasedOutlierDetection".

The Density based approach says:
This operator is a DB outlier detection algorithm which calculates the DB(p,D)-outliers for an ExampleSet passed to the operator. DB(p,D)-outliers are Distance based outliers according to Knorr and Ng. A DB(p,D)-outlier is an object to which at least a proportion of p of all objects are farer away than distance D. It implements a global homogenous outlier search.
Is it using distance measure? Or just to calculate the distances in the beginning and the rest procedure deals with the density approach? The "DistanceBasedOutlierDetection" deals with distances and the "LOFOutlierDetection" is based on density based methods. My ambiguity is with the "DensityBasedOutlierDetection".

Thanks,
Shubha
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