Jasvinder Singh, Garvit Joshi, H. Tiwari, Ishita Tiwari
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Applied Machine Learning for and Analysis of RR Lyrae Variable Stars
Machine Learning is being used extensively in various fields. From health, physical systems and astronomy, the scope of automating process and analyzing data has no limits, added by the sheer amount of computation prowess. In this paper, we will use various Machine Learning Algorithms to perform supervised classification of one of the most relevant and unique stars of the Milky Way Galaxy - RR Lyrae. We will discuss the performance of each algorithm and use Type I and Type II errors to improve their performance. Furthermore, we will visualize and analyze the data to mine meaningful information.
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