Abstract
In these years, we often deal with an enormous amount of data or a data stream in a large variety of pattern recognition tasks. As a promising approach for economising the amount, we have previously defined a volume prototype as a geometric configuration that represents some data points inside and proposed a single-pass algorithm for finding them. In this paper, we analyze the convergence behavior of volume prototypes in high-dimensional cases. In addition, we show the applicability of volume prototypes to high-dimensional classification problems.
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© 2008 Springer-Verlag Berlin Heidelberg
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Sato, M., Kudo, M., Toyama, J. (2008). Behavior Analysis of Volume Prototypes in High Dimensionality. In: da Vitoria Lobo, N., et al. Structural, Syntactic, and Statistical Pattern Recognition. SSPR /SPR 2008. Lecture Notes in Computer Science, vol 5342. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-89689-0_91
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DOI: https://doi.org/10.1007/978-3-540-89689-0_91
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-89688-3
Online ISBN: 978-3-540-89689-0
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