Abstract
Several non-parametric regression methods with various dependent variables that are possibly related are explored. The techniques which produce the best results in the simulations are those which incorporate the observations of the other response variables in the estimator. Compared to analogous single-response techniques, this approach results in a significant reduction in the quadratic error in the response.
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Matías, J.M. (2005). Multi-output Nonparametric Regression. In: Bento, C., Cardoso, A., Dias, G. (eds) Progress in Artificial Intelligence. EPIA 2005. Lecture Notes in Computer Science(), vol 3808. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11595014_29
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DOI: https://doi.org/10.1007/11595014_29
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-30737-2
Online ISBN: 978-3-540-31646-6
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