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Fusing Decision Trees Based on Genetic Programming for Classification of Microarray Datasets

机译:基于遗传规划的融合决策树用于微阵列数据集分类

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In this paper, a genetic programming(GP) based new ensemble system is proposed, named as GPES. Decision tree is used as base classifier, and fused by GP with three voting methods: min, max and average. In this way, each individual of GP acts as an ensemble system. When the evolution process of GP ends, the final ensemble committee is selected from the last generation by a forward search algorithm. GPES is evaluated on microarray datasets, and results show that this ensemble system is competitive compared with other ensemble systems.
机译:本文提出了一种基于遗传程序设计(GP)的新集成系统,命名为GPES。决策树用作基本分类器,并由GP与三种投票方法(最小,最大和平均值)融合。这样,GP的每个人都可以作为一个整体系统。当GP的演化过程结束时,通过前向搜索算法从最后一代中选择最终的合奏委员会。 GPES在微阵列数据集上进行了评估,结果表明该集成系统与其他集成系统相比具有竞争力。

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