Abstract
In this paper we carry out an statistical study of the performance of the μ-GA ELM algorithm in regression problems. Up until now, the performance of the the μ-GA ELM have not been characterized, and only a traditional evolutionary ELM have been proposed in the literature, and tested in synthetic problems. In this paper we analyze the performance of the μ-GA ELM in small 1-dimensional problems, where our results agree with the ones in previous works in the literature, and also in large real problems, where we will show that the behavior of the algorithm is worse in many cases than that of the ELM, what is a completely novel result.
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Paniagua-Tineo, A., Salcedo-Sanz, S., Ortiz-García, E.G., Gascón-Moreno, J., Saavedra-Moreno, B., Portilla-Figueras, J.A. (2011). On the Performance of the μ-GA Extreme Learning Machines in Regression Problems. In: Cabestany, J., Rojas, I., Joya, G. (eds) Advances in Computational Intelligence. IWANN 2011. Lecture Notes in Computer Science, vol 6692. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21498-1_20
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DOI: https://doi.org/10.1007/978-3-642-21498-1_20
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-21497-4
Online ISBN: 978-3-642-21498-1
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