Hybrid Clustering Algorithm based on Mahalanobis Distance and MST

@inproceedings{Kumari2012HybridCA,
  title={Hybrid Clustering Algorithm based on Mahalanobis Distance and MST},
  author={V. Valli Kumari and R. Raju and Azad Naik},
  year={2012}
}
Most of the clustering algorithms are based on Euclidean distance as measure of similarity between data objects. Theses algorithms also require initial setting of parameters as a prior, for example the number of clusters. The Euclidean distance is very sensitive to scales of variables involved and independent of correlated variables. To conquer these drawbacks a hybrid clustering algorithm based on Mahalanobis distance is proposed in this paper. The reason for the hybridization is to relieve… CONTINUE READING