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Classification of Prostate Cancer Patients and Healthy Individuals by Means of a Hybrid Algorithm Combing SVM and Evolutionary Algorithms

机译:基于支持向量机和进化算法的混合算法对前列腺癌患者和健康个体的分类

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摘要

This research presents a new hybrid algorithm able to select a set of features that makes it possible to classify healthy individuals and those affected by prostate cancer. In this research the feature selection is performed with the help of evolutionary algorithms. This kind of algorithms, have proven in previous researches their ability for obtaining solutions for optimization problems in very different fields. In this study, a hybrid algorithm based on evolutionary methods and support vector machine is developed for the selection of optimal feature subsets for the classification of data sets. The results of the algorithm using a reduced data set demonstrates the performance of the method when compared with non-hybrid methodologies.
机译:这项研究提出了一种新的混合算法,该算法能够选择一组特征,从而可以对健康个体和受前列腺癌影响的个体进行分类。在这项研究中,特征选择是在进化算法的帮助下进行的。这种算法已在先前的研究中证明了其在非常不同的领域中获得优化问题解决方案的能力。在这项研究中,开发了一种基于进化方法和支持向量机的混合算法,用于选择用于数据集分类的最佳特征子集。与非混合方法相比,使用减少的数据集的算法结果证明了该方法的性能。

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