Neutron star classifier with a multilayer neural network using R
Abstract
In this work what will be done is to analyze the exercise "Neutron star classifier" for this, the first thing will be presented a brief introduction of our proposed exercise, then we will carry out the basic concepts of a neural network since it is the one chosen for the resolution of this exercise, but this is classified by artificial neural networks according to the network topology and networks according to the learning method, where it has been seen to be convenient to do it with the multilayer neural network - multilayer perceptron, then you will have the data cleaning, transformation of cases, selection of cases, selection of a data language as well as the packages, framework libraries that will be used, to then carry out the execution of the training technique, trained model, verification phase, analysis of the results and analysis of the client; finally come to conclusions.
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References
C. C. Aggarwal, “Neural networks and deep learning,” Springer, vol. 10, pp. 978–3, 2018.
J. Schmidhuber, “Deep learning in neural networks: An overview,” Neural networks, vol. 61, pp. 85–117, 2015.
V. Kreinovich, “From traditional neural networks to deep learning: towards mathematical foundations of empirical successes,” in Recent Developments and the New Direction in Soft-Computing Foundations and Applications, Springer, 2021, pp. 387–397.
S. R. Young, D. C. Rose, T. P. Karnowski, S.-H. Lim, and R. M. Patton, “Optimizing deep learning hyper-parameters through an evolutionary algorithm,” in Proceedings of the Workshop on Machine Learning in High-Performance Computing Environments, 2015, pp. 1–5.
J. Allaire, “RStudio: integrated development environment for R,” Boston, MA, vol. 770, p. 394, 2012.
J. M. Elias, “Webinar sobre la docencia en línea con RStudio Cloud,” IDP: revista d’Internet, dret i política, no. 31, 2020.
S. Aiello, E. Eckstrand, A. Fu, M. Landry, and P. Aboyoun, “Machine Learning with R and H2O,” H2O booklet, vol. 550, 2016.
- Conceptualization
- Data curation
- Investigation
- Methodology
- Software
- Validation
- Writing - original draft
- Conceptualization
- Data curation
- Investigation
- Methodology
- Software
- Validation
- Writing - original draft
- Conceptualization
- Data curation
- Investigation
- Methodology
- Software
- Validation
- Writing - original draft
- Conceptualization
- Data curation
- Investigation
- Methodology
- Software
- Validation
- Writing - original draft
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