Semantic Scholar Open Access 2020 1 sitasi

Machine Learning Approaches for Supernovae Classification

Surbhi Agrawal Kakoli Bora S. Routh

Abstrak

In this chapter, authors have discussed few machine learning techniques and their application to perform the supernovae classification. Supernovae has various types, mainly categorized into two important types. Here, focus is given on the classification of Type-Ia supernova. Astronomers use Type-Ia supernovae as “standard candles” to measure distances in the Universe. Classification of supernovae is mainly a matter of concern for the astronomers in the absence of spectra. Through the application of different machine learning techniques on the data set authors have tried to check how well classification of supernovae can be performed using these techniques. Data set used is available at Riess et al. (2007) (astro-ph/0611572).

Topik & Kata Kunci

Computer Science

Penulis (3)

Surbhi Agrawal

Kakoli Bora

S. Routh

Format Sitasi

APA MLA BibTeX

Agrawal, S., Bora, K., Routh, S. (2020). Machine Learning Approaches for Supernovae Classification. https://doi.org/10.4018/978-1-5225-2498-4.CH009

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Informasi Jurnal

Tahun Terbit: 2020
Bahasa: en
Total Sitasi: 1×
Sumber Database: Semantic Scholar
DOI: 10.4018/978-1-5225-2498-4.CH009
Akses: Open Access ✓