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Stumbled across this article about "cliques" and "clique density" as an improvement to k-NN. Anyone see this before and/or implemented it?
http://www.datasciencecentral.com/profiles/blogs/nice-generalization-of-the-k-nn-clustering-algorithm
Scott
This seems quite similar conceptually to the Cluster-Based Local Outlier Factor approach, which is used in outlier detection (and is included in the free anomaly detection extension in RapidMiner). I'd have to dig in further to see how they are different, or have an implementation of the k-NC to compare the outcomes. But if you are interested in this then you may want to check out CB-LOF.
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