Abstract

The term “exoplanet” holds significant interest in contemporary science. A planet orbiting a star beyond the solar system serves as a foundation for exploring concepts of alien life in the universe. This study utilizes data from Bryson et al. (2020), drawn from the Kepler DR25 planet candidate catalog, to focus on habitable rocky exoplanets with high inclusion probability. Intrinsic groupings among these exoplanets are analyzed based on their physical attributes. The optimal number of planetary groups is identified through the maximum number of clustering indices, and the exoplanets are grouped using the most appropriate clustering technique. The groups primarily differ based on the host star’s temperature and the orbital period of the exoplanets, two critical physical attributes. Best-fitted multivariate probability distributions and their estimated parameters are employed to classify unknown habitable rocky exoplanets into the identified groups. A classification rule based on the maximum probability density value is proposed and applied, yielding satisfactory classification results.

Author: Sushovon Jana, Hrittik Banerjee

Received on: October, 2023

Accepted on: May, 2025