Abstract
In this paper, BTW, a new method for similar case search, is presented. The main objective is to optimize the metrics employed in classical approaches in order to obtain an intense compression in the data and a deterministic real-time behavior; and without compromising the performance of the classification task. BTW tries to conjugate the best of three well-known techniques: Nearest Neighbor, Fisher discriminant and optimization.
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© 2012 Springer-Verlag Berlin Heidelberg
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Ocejo, J.R., Bukubiye, E.K. (2012). BTW: A New Distance Metric for Classification. In: Omatu, S., De Paz Santana, J., González, S., Molina, J., Bernardos, A., Rodríguez, J. (eds) Distributed Computing and Artificial Intelligence. Advances in Intelligent and Soft Computing, vol 151. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-28765-7_84
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DOI: https://doi.org/10.1007/978-3-642-28765-7_84
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-28764-0
Online ISBN: 978-3-642-28765-7
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