计算机工程2012，Vol.38Issue(4)：67-69,3.
一种改进的少数类样本过抽样算法
Improved Over-sampling Algorithm of Minority Class Sample
摘要
Abstract
Aiming at the classification of the skewed dataset, this paper proposes an improved over-sampling algorithm of minority class sample, named B-ISMOTE. It improves the data unbalanced distribution of degree through randomized interpolation to produce virtual minority class instances in the sphere space, which constitute of the borderline minority class instances and its nearest neighbor. Experimental results on the real datasets show that compared with SMOTE algorithm and B-SMOTE algorithm, B-ISMOTE algorithm has better classification performance.关键词
偏斜数据集/分类/过抽样/虚拟实例/n维球体空间Key words
skewed dataset/ classification/ over-sampling/ virtual instance/ n dimension sphere space分类
信息技术与安全科学引用本文复制引用
许丹丹,蔡立军,王勇..一种改进的少数类样本过抽样算法[J].计算机工程,2012,38(4):67-69,3.基金项目
国家自然科学基金资助项目(60873196) （60873196）
