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Fuzzy and SVM Based Classification Model to Classify Spectral Objects in Sloan Digital Sky
Arodh Lal Karn, Carlos Andres Tavera Romero, Sudhakar Sengan, Abolfazl Mehbodniya, Julian L. Webber, Denis A. Pustokhin and Frank-Detlef Wende IEEE Access 10 101276 (2022) https://doi.org/10.1109/ACCESS.2022.3207480
Smart Intelligent Computing and Applications, Volume 1
Mariyam Ashai, Rhea Gautam Mukherjee, Sanjana P. Mundharikar, Vinayak Dev Kuanr and R. Harikrishnan Smart Innovation, Systems and Technologies, Smart Intelligent Computing and Applications, Volume 1 282 377 (2022) https://doi.org/10.1007/978-981-16-9669-5_34
Effectively using unsupervised machine learning in next generation astronomical surveys
Identification of BASS DR3 sources as stars, galaxies, and quasars by XGBoost
Changhua Li, Yanxia Zhang, Chenzhou Cui, et al. Monthly Notices of the Royal Astronomical Society 506(2) 1651 (2021) https://doi.org/10.1093/mnras/stab1650
Identification of emission-line stars in transition phase from pre-main sequence to main sequence
Suman Bhattacharyya, Blesson Mathew, Gourav Banerjee, et al. Monthly Notices of the Royal Astronomical Society 507(3) 3660 (2021) https://doi.org/10.1093/mnras/stab2385
Efficient selection of quasar candidates based on optical and infrared photometric data using machine learning
Dongwei Fan, Xue-bing Wu, Yongheng Zhao, et al. Monthly Notices of the Royal Astronomical Society 485(4) 4539 (2019) https://doi.org/10.1093/mnras/stz680
Probabilistic Random Forest: A Machine Learning Algorithm for Noisy Data Sets
Bo Han, Yan-Xia Zhang, Shou-Bo Zhong and Yong-Heng Zhao Research in Astronomy and Astrophysics 16(11) 178 (2016) https://doi.org/10.1088/1674-4527/16/11/178
Eduardo Machado, Marcello Serqueira, Eduardo Ogasawara, Ricardo Ogando, Marcio A. G. Maia, Luiz Nicolaci da Costa, Riccardo Campisano, Gustavo Paiva Guedes and Eduardo Bezerra 123 (2016) https://doi.org/10.1109/IJCNN.2016.7727189
OF GENES AND MACHINES: APPLICATION OF A COMBINATION OF MACHINE LEARNING TOOLS TO ASTRONOMY DATA SETS
S. Heinis, S. Kumar, S. Gezari, W. S. Burgett, K. C. Chambers, P. W. Draper, H. Flewelling, N. Kaiser, E. A. Magnier, N. Metcalfe and C. Waters The Astrophysical Journal 821(2) 86 (2016) https://doi.org/10.3847/0004-637X/821/2/86
Stellar spectra association rule mining method based on the weighted frequent pattern tree
Jiang-Hui Cai, Xu-Jun Zhao, Shi-Wei Sun, Ji-Fu Zhang and Hai-Feng Yang Research in Astronomy and Astrophysics 13(3) 334 (2013) https://doi.org/10.1088/1674-4527/13/3/008
Star-galaxy separation in the AKARI NEP deep field
QUASI-STELLAR OBJECT SELECTION ALGORITHM USING TIME VARIABILITY AND MACHINE LEARNING: SELECTION OF 1620 QUASI-STELLAR OBJECT CANDIDATES FROM MACHO LARGE MAGELLANIC CLOUD DATABASE
Miguel Á. Montero, Roberto Ruíz, Miguel García-Torres and Luis M. Sarro Lecture Notes in Computer Science, Trends in Applied Intelligent Systems 6096 611 (2010) https://doi.org/10.1007/978-3-642-13022-9_61
Automated spectral classification using template matching