Abstract The key to the success of an Error-Correcting Output Code (ECOC) algorithm is the effective codematrix, which represents a set of class reassignment schemes for decomposing a multiclass problem into a set of binary class problems. This paper proposes a new method, which uses Ternary digit Operators based Genetic Programming (GP) to generate effective ECOC codematrix (TOGP-ECOC for short). In our GP, each terminal node stores a ternary digit string, representing a column and a related feature subset; each non-terminal node represents a ternary digit operator, which produces a new column based on its child nodes. In this way, each individual is interpreted as an ECOC codematrix along with a set of corresponding feature subsets, serving the solution for the multiclass classification task. When a new individual is produced, a legality checking process is carried out to verify whether the transformed codematrix follows the ECOC constraints. The illegal one is corrected according to different strategies. Besides, a local optimization algorithm is designed to prune redundant columns and improve the performance of each individual. Our experiments compared TOGP-ECOC with some well known ECOC algorithms on various data sets, and the results confirm the superiority of our algorithm. Our source code is available at: https://github.com/MLDMXM2017/TOGP-ECOC .

中文翻译：

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一种基于遗传规划和三元运算符的新型纠错输出码

摘要 纠错输出码 (ECOC) 算法成功的关键是有效的代码矩阵，它表示一组用于将多类问题分解为一组二元类问题的类重新分配方案。本文提出了一种新的方法，它使用基于三元数字算子的遗传编程（GP）来生成有效的ECOC码矩阵（简称TOGP-ECOC）。在我们的GP中，每个终端节点存储一个三进制数字串，代表一列和相关的特征子集；每个非终端节点代表一个三元数字运算符，它根据其子节点生成一个新列。通过这种方式，每个个体都被解释为一个 ECOC 代码矩阵以及一组相应的特征子集，为多类分类任务提供解决方案。当一个新的个体产生时，执行合法性检查过程以验证转换后的代码矩阵是否遵循 ECOC 约束。根据不同的策略纠正非法的。此外，设计了一种局部优化算法来修剪冗余列并提高每个人的表现。我们的实验在各种数据集上将 TOGP-ECOC 与一些众所周知的 ECOC 算法进行了比较，结果证实了我们算法的优越性。我们的源代码位于：https://github.com/MLDMXM2017/TOGP-ECOC。我们的实验在各种数据集上将 TOGP-ECOC 与一些众所周知的 ECOC 算法进行了比较，结果证实了我们算法的优越性。我们的源代码位于：https://github.com/MLDMXM2017/TOGP-ECOC。我们的实验在各种数据集上将 TOGP-ECOC 与一些众所周知的 ECOC 算法进行了比较，结果证实了我们算法的优越性。我们的源代码位于：https://github.com/MLDMXM2017/TOGP-ECOC。