System Evaluation of Ternary Error-Correcting Output Codes for Multiclass Classification Problems
System Evaluation of Ternary Error-Correcting Output Codes for Multiclass Classification Problems
复制标题
多类分类问题三元纠错输出码的系统评估
DOI：
10.1109/smc.2019.8914295
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发表时间：
2019
期刊：
影响因子：
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通讯作者：
and H. Inazumi
中科院分区：
文献类型：
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作者：
S. Hirasawa;G. Kumoi;H. Yagi;M. Kobayashi;M. Goto;T. Sakai;and H. Inazumi
为了解决多重分类问题，许多研究都致力于使用二进制分类器，这些系统被称为二进制纠错输出码（binary ECOC）。作为二进制ECOC的扩展版本，我们还讨论了ternaryECOC，其中三元分类器在元素为1时将数据分类为正例，当元素为0时将数据分类为负例，当元素为时不分类。本文从基于率失真函数的系统评价模型的角度对三元ECOC系统进行了讨论。首先，我们讨论了一个由M行N列的三元矩阵W给出的长度为N的M个码字表。接下来，利用日本广泛使用的多类文档分类基准数据，实验研究了给定M的分类错误概率p与三元分类器个数N之间的关系。此外，通过假设分类数据模型的M维正态分布，还检查了给定M的ped和N之间的关系。最后，通过系统评价模型表明，当M变大时，三元ECOC系统具有理想的“柔性”、“弹性”和“有效弹性”等特性。
To solve multiple classification problems with3) categories, many studies have been devoted usingbinaryclassifiers, where these systems are known as binary Error-Correcting Output Codes (binary ECOC). As an extended version of the binary ECOC, the ternaryECOC have also been discussed, where ternary classifiers classify data into positive examples when the element is 1, into negative examples when the element is 0, and no classification when the element is. In this paper, we discuss the ternary ECOC system from the view point of the system evaluation model based on rate-distortion function. First, we discuss a table of M code words with length N which is given by a ternary matrix W of M rows and N columns. Next, by leveraging the benchmark data for multiclass document classification which is widely used in Japan, the relationships between the probability of classification error Peand the number of the ternary classifiers N for a given M are experimentally investigated. In addition, by assuming the M-dimensional Normal distribution for a classification data model, the relationship between Peand N for a given M is also examined. Finally, we show by the system evaluation model that the ternary ECOC systems have desirable properties such as “Flexible”, “Elastic”, and “Effective Elastic”, when M becomes large.