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A Genetic Programming Ensemble Approach to Cancer Microarray Data Classification

机译:癌症微阵列数据分类的遗传编程集合方法

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This paper presents a method for building an ensemble of classifiers for cancer microarray data. The proposed method exploits the advantage of a clustering technique, namely K-means clustering, combined with a feature selection technique, namely SNR feature selection. An evolutionary algorithm, namely Genetic Programming, is used to construct a number of classifiers which are assembled into an ensemble. The performance of the proposed method was tested on six cancer microarray data sets. The experimental results indicate that the proposed method yields a good prediction accuracy with a small standard deviation.
机译:本文介绍了构建癌症微阵列数据分类器的集合的方法。所提出的方法利用聚类技术的优点,即K-Means聚类,与特征选择技术组合,即SNR特征选择。一种进化算法,即遗传编程,用于构建组装成集合的许多分类器。在六种癌症微阵列数据集上测试了所提出的方法的性能。实验结果表明,该方法具有良好的预测精度,具有小的标准偏差。

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