Classifying Exoplanets with Gaussian Mixture Model

TL;DR

This paper applies Gaussian Mixture Models to classify exoplanets based on density and Earth similarity index, finding mixed evidence for the number of categories and emphasizing the importance of multi-dimensional analysis.

Contribution

It introduces a GMM-based classification of exoplanets using density and Earth similarity, extending previous one-dimensional methods with a two-dimensional approach.

Findings

Two components favored by AIC for density alone

Three components favored by BIC for density alone

Decisive evidence for three categories in two-dimensional classification

Abstract

Recently, Odrzywolek and Rafelski (arXiv:1612.03556) have found three distinct categories of exoplanets, when they are classified based on density. We first carry out a similar classification of exoplanets according to their density using the Gaussian Mixture Model, followed by information theoretic criterion (AIC and BIC) to determine the optimum number of components. Such a one-dimensional classification favors two components using AIC and three using BIC, but the statistical significance from both the tests is not significant enough to decisively pick the best model between two and three components. We then extend this GMM-based classification to two dimensions by using both the density and the Earth similarity index (arXiv:1702.03678), which is a measure of how similar each planet is compared to the Earth. For this two-dimensional classification, both AIC and BIC provide decisive evidence in favor of three components.