Separability of ternary codes for sparse designs of error-correcting output codes
Separability of ternary codes for sparse designs of error-correcting output codes
复制标题
DOI：
10.1016/j.patrec.2008.10.002
复制
发表时间：
2009-02-01
影响因子：
5.1
通讯作者：
Radeva, Petia
中科院分区：
文献类型：
--
作者：
Escalera, Sergio;Pujol, Oriol;Radeva, Petia
纠错输出码（ECOC）是一个成功的框架来处理多类分类问题的基础上组合的二进制分类器。随着二进制ECOC到三进制ECOC框架的扩展，已经提出了ECOC设计，以便更好地适应数据的分布。为了解码三进制矩阵，最近的作品重新定义了许多解码策略，制定处理只有两个符号。然而，编码步骤也受到影响，因此，需要重新考虑。在本文中，我们提出了一个新的公式的三元ECOC距离和纠错能力的三元ECOC框架。在此基础上，重点研究了如何设计防止编码歧义的编码矩阵，并提出了一种新的三进制距离最大化的稀疏随机编码矩阵。在广泛的UCI机器学习库数据集和真实的速度交通标志分类问题的结果表明，当编码设计满足新的三元措施，获得显着的性能改善独立的解码策略。(C)2008 Elsevier B.V.保留所有权利。
Error-correcting output codes (ECOC) represent a successful framework to deal with multi-class categorization problems based on combining binary classifiers. With the extension of the binary ECOC to the ternary ECOC framework, ECOC designs have been proposed in order to better adapt to distributions of the data. In order to decode ternary matrices, recent works redefined many decoding strategies that were formulated to deal with just two symbols. However, the coding step also is affected, and therefore, it requires to be reconsidered. In this paper, we present a new formulation of the ternary ECOC distance and the error-correcting capabilities in the ternary ECOC framework. Based on the new measure, we stress on how to design coding matrices preventing codification ambiguity and propose a new sparse random coding matrix with ternary distance maximization. The results on a wide set of UCI Machine Learning Repository data sets and in a real speed traffic sign categorization problem show that when the coding design satisfies the new ternary measures, significant performance improvement is obtained independently of the decoding strategy applied. (C) 2008 Elsevier B.V. All rights reserved.