Behavior Analysis of Volume Prototypes in High Dimensionality

Authors:
Maiko Sato;Mineichi Kudo;Jun Toyama
Affiliations:
Division of Computer Science Graduate School of Information Science and Technology, Hokkaido University, Sapporo, Japan 060-0814;Division of Computer Science Graduate School of Information Science and Technology, Hokkaido University, Sapporo, Japan 060-0814;Division of Computer Science Graduate School of Information Science and Technology, Hokkaido University, Sapporo, Japan 060-0814
Venue:
SSPR & SPR '08 Proceedings of the 2008 Joint IAPR International Workshop on Structural, Syntactic, and Statistical Pattern Recognition
Year:
2008

Citing 2
Cited 0

Introduction to statistical pattern recognition (2nd ed.)

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Fuzzy clustering with volume prototypes and adaptive cluster merging

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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.