Clustering high dimensional data using subspace and projected clustering algorithms

  title={Clustering high dimensional data using subspace and projected clustering algorithms},
  author={Rahmat Widia Sembiring and Jasni Mohamad Zain and Abdullah Embong},
Problem statement: Clustering has a number of techniques that have been developed in statistics, pattern recognition, data mining, and other fields. Subspace clustering enumerates clusters of objects in all subspaces of a dataset. It tends to produce many over lapping clusters. Approach: Subspace clustering and projected clustering are research areas for clustering in high dimensional spaces. In this research we experiment three clustering oriented algorithms, PROCLUS, P3C and STATPC. Results… CONTINUE READING
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