| 基于核函数拟合的非平衡数据分类方法 |
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| 引用本文： | 马胜祥,马建庆,杨明. 基于核函数拟合的非平衡数据分类方法[J]. 计算机应用与软件, 2010, 27(4): 177-179 |
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| 作者姓名： | 马胜祥 马建庆 杨明 |
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| 作者单位： | 复旦大学计算机与信息技术系,上海,200433 |
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| 摘 要： | 在数据分类算法的实际应用中,经常会遇到数据不平衡的问题(即正负样本的数目相差极大)。标准的分类算法在处理这一问题时,往往很难达到令人满意的性能。提出一种新的方法,通过对正负样本分别进行核函数拟合,根据拟合好的核函数对未知样本进行预测。在UCI标准数据集的仿真实验结果表明,该方法能有效地处理非平衡数据问题。
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| 关 键 词： | 非平衡数据 核函数 拟合 |
A FITTED KERNEL FUNCTION BASED CLASSIFICATION METHOD FOR IMBALANCED DATASET |
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| Ma Shengxiang,Ma Jianqing,Yang Ming. A FITTED KERNEL FUNCTION BASED CLASSIFICATION METHOD FOR IMBALANCED DATASET[J]. Computer Applications and Software, 2010, 27(4): 177-179 |
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| Authors: | Ma Shengxiang Ma Jianqing Yang Ming |
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| Affiliation: | Department of Computing and Information Technology/a>;Fudan University/a>;Shanghai 200433/a>;China |
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| Abstract: | The data imbalance problem,where the difference between numbers of positive samples and negative samples are much great,frequently occurs in practical application of data classification algorithms.Standard classification algorithm is hard to perform satisfactorily when dealing with this.In this paper,the author propose a new method,which fits the positive samples and negative samples respectively with kernel functions and predicts the unknown samples according to the fitted kernel function.Simulation experi... |
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| Keywords: | Imbalanced data Kernel function Fitting |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
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