The paper proposes a mathematical model for automated classification of space objects and redshift value estimation by applying the Sloan Digital Sky Server (SDSS) Dataset. Redshift is a measure of how fast a celestial object is moving relative to us, which is a basis for universe expansion. Furthermore, this paper is an attempt at Universe mapping in 2-Dimension as well as an interactive 3-Dimensional View.

Keywords — Classification, Hubble’s Law, K Nearest Neighbours, Random Forest, Redshift, Space Objects, 2D mapping, 3D mapping of universe.;