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A new minority kind of sample sampling method based on genetic algorithm and K-means cluster

机译:基于遗传算法和K-means聚类的少数样本采样新方法

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摘要

In view of the classification favors seriously to the most kinds when we use the traditional sorter to classify the imbalanced data set and the errors of classification of minority kind is big, A new minority kind of sample sampling method based on genetic algorithm and K-means cluster is proposed. First the method clusters and groups the minority kind of sample through K-means algorithm, then gains the new sample in each cluster through the genetic algorithm and the valid confirmation is proceed. Finally, The validity of experimental results is proved through using SVM and KNN sorter.
机译:鉴于使用传统的分类器对不平衡数据集进行分类时对分类的重视程度最高,少数种类的分类误差较大,一种基于遗传算法和K-means的小样本新采样方法提出集群。该方法首先通过K-means算法对少数样本进行聚类和分组,然后通过遗传算法获得每个聚类中的新样本,并进行有效的确认。最后,通过支持向量机和KNN排序器证明了实验结果的有效性。

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