Abstract
Classification of galaxies has been carried out by using two recently developed methods, viz., Independent Component Analysis (ICA) with K-means clustering and Clustering in Arbitrary Subspace based on Hough Transform (CASH) for different data sets. The first two sets are consisting of dwarf galaxies and their globular clusters whose distributions are non Gaussian in nature. The third one is a larger one containing a wider range of galaxies consisting of dwarfs to giants in 56 clusters of galaxies. Morphological classification of galaxies are subjective in nature and as a result can not properly explain the formation mechanism and other related issues under the influence of different correlated variables through a proper scientific approach. Hence objective classification by using the above mentioned methods are preferred to overcome the loopholes.`
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Chattopadhyay, A.K., Chattyopadhyay, T., De, T., Mondal, S. (2013). Independent Component Analysis for Dimension Reduction Classification: Hough Transform and CASH Algorithm. In: Hilbe, J. (eds) Astrostatistical Challenges for the New Astronomy. Springer Series in Astrostatistics, vol 1. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-3508-2_9
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