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Feature Selection of Microarray Data using Bacterial Foraging Optimization

机译:利用细菌觅食优化技术选择微阵列数据

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This study aims at finding the genes responsible for lung cancer using bacterial foraging optimization. Microarray datasets can be used to predict the presence of cancer, the type of cancer, its stage etc. Microarray datasets available have large number of features and few samples. Bacterial foraging optimization algorithm has been used in our study for feature selection on lung cancer dataset. BFO algorithm selects few genes from the available set. The reduced dataset is then used for designing a classifier using support vector machines which gives an accuracy of about 99% classifying only one sample inaccurately.
机译:这项研究旨在通过细菌觅食优化找到导致肺癌的基因。微阵列数据集可用于预测癌症的存在,癌症的类型,癌症的分期等。可用的微阵列数据集具有大量特征且样本很少。在我们的研究中,细菌觅食优化算法已用于肺癌数据集的特征选择。 BFO算法从可用集中选择很少的基因。缩减后的数据集随后用于使用支持向量机设计分类器,该分类器仅将一个样本进行不准确分类的准确率约为99%。

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