论文标题
用于解决分类问题的多表达编程
Multi Expression Programming for solving classification problems
论文作者
论文摘要
多表达编程（MEP）是一种基因编程变体，它在单个染色体中编码多个溶液。本文介绍并深入介绍了在\ textIt {Multi Solutions of MEP的\ textIt {多类解决方案}范式中解决二进制和多类分类问题的几种策略。进行各种分类问题的广泛实验。与其他用于比较的方法相比，MEP表现出类似或更好的性能（即人工神经网络和线性遗传编程）。
Multi Expression Programming (MEP) is a Genetic Programming variant which encodes multiple solutions in a single chromosome. This paper introduces and deeply describes several strategies for solving binary and multi-class classification problems within the \textit{multi solutions per chromosome} paradigm of MEP. Extensive experiments on various classification problems are performed. MEP shows similar or better performances than other methods used for comparison (namely Artificial Neural Networks and Linear Genetic Programming).
