Subspace clustering based on compressibility

被引：0

作者：

Narahashi, M ^{[1
]}

Suzuki, E ^{[1
]}

机构：

[1] Yokohama Natl Univ, Yokohama, Kanagawa 2408501, Japan

来源：

DISCOVERY SCIENCE, PROCEEDINGS | 2002年 / 2534卷

关键词：

D O I：

暂无

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

In this paper, we propose a subspace clustering method based on compressibility. It is widely accepted that compressibility is deeply related to inductive learning. We have come to believe that compressibility is promising as an evaluation criterion in subspace clustering, and propose SUBCCOM in order to verify this belief. Experimental evaluation employs both artificial and real data sets.

引用

页码：435 / 440

页数：6

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