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Cluster analysis is the distribution of objects into different groups or moreprecisely the partitioning of a data set into subsets (clusters) so that thedata in subsets share some common trait according to some distance measure.Unlike classi cation, in clustering one has to rst decide the optimum number ofclusters and then assign the objects into different clusters. Solution of suchproblems for a large number of high dimensional data points is quitecomplicated and most of the existing algorithms will not perform properly. Inthe present work a new clustering technique applicable to large data set hasbeen used to cluster the spectra of 702248 galaxies and quasars having 1540points in wavelength range imposed by the instrument. The proposed techniquehas successfully discovered ve clusters from this 702248X1540 data matrix.

Clustering large number of extragalactic spectra of galaxies and quasars through canopies