Star-Galaxy classification using machine learning algorithms and deep learning

Abstract

Cosmology is the study of the universe comprising stars and galaxies. Advancement in the telescope has made it possible to capture high-resolution images, which can be analyzed using machine learning (ML) algorithms. This paper classifies the star galaxy dataset into two classes: star and galaxy using ML algorithms and compares their classification performance. It is observed that random forest provides better accuracy of 78% as compared to other ML classifiers. Further to improve the classification accuracy, we proposed a CNN (Convolution Neural Network) model and achieved an accuracy of 92.44%. Since the CNN model itself extracts the characteristics, it exhibits superior classification accuracy.