| 面向不均衡数据集的ISMOTE算法 |
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| 引用本文： | 许丹丹,王勇,蔡立军.面向不均衡数据集的ISMOTE算法[J].计算机应用,2011,31(9):2399-2401. |
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| 作者姓名： | 许丹丹 王勇 蔡立军 |
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| 作者单位： | 1. 西北工业大学 理学院，西安 7101292. 西北工业大学 计算机学院，西安 710072 |
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| 基金项目： | 国家自然科学基金资助项目(60873196) |
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| 摘 要： | 为了提高不均衡数据集中少数类的分类性能，提出ISMOTE算法。它是在少数类实例及其最近邻少数类实例构成的n维球体内进行随机插值，从而来改进数据分布的不均衡程度。通过实际数据集上的实验，与SMOTE算法和直接分类不均衡数据算法的性能比较结果表明,ISMOTE算法具有更高的分类精度，可以有效地改进分类器的性能。
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| 关 键 词： | 不均衡数据集 分类 虚拟实例 少数类过抽样算法 |
| 收稿时间： | 2011-03-15 |
| 修稿时间： | 2011-05-17 |
ISMOTE algorithm for imbalanced data sets |
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| XU Dan-dan,WANG Yong,CAI Li-jun.ISMOTE algorithm for imbalanced data sets[J].journal of Computer Applications,2011,31(9):2399-2401. |
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| Authors: | XU Dan-dan WANG Yong CAI Li-jun |
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| Affiliation: | 1. School of Science, Northwestern Polytechnical University, Xi'an Shaanxi 710129, China2. School of Computer Science and Technology, Northwestern Polytechnical University, Xi'an Shaanxi 710072, China |
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| Abstract: | In order to improve the classification performance of minority class instances in imbalanced dataset, a new algorithm named ISMOTE (Improved Synthetic Minority Over-sampling TEchnique) was proposed. ISMOTE improved the imbalanced distribution of data through randomizing interpolation in the ball space constituted of the minority class instances and its nearest neighbor. The experiment was given on real data set. The experimental results show that the ISMOTE has substantial advantages over SMOTE (Synthetic Minority Over-sampling Technique) and direct classifying imbalanced data algorithm in prediction accuracy, and it can effectively improve the performance of classifier. |
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| Keywords: | imbalanced dataset classification virtual instances Synthetic Minority Over-sampling TEchnique (SMOTE) |
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