Behavior Analysis of Volume Prototypes in High Dimensionality
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.