基于特征选择的过抽样算法的研究

doi:10.3969/j.issn.1000-0801.2012.01.017

Abstract

Abstract:

To significantly improve the classification performance of the minority class,we present an over-sampling method based on feature selection.Firstly,feature selection is performed on the training data set in order to select a set of key columns.Then minority class samples are produced using selected key columns,and each sample consists of two kinds of features.One type of features is characteristic value that is corresponding to the selected key columns,the others is generated according to the principle of SMOTE.Comparing to SMOTE algorithm,results show that the new method performs better than SMOTE,and it can effectively reduce the imbalance of data and improve the classification accuracy of the minority class.

Key words: imbalanced data set, feature selection, over sampling, genetic algorithm

Huijuan Lu,Jinwei Zhang,Jinwei Zhang,Jinwei Zhang,Xiaoping Ma,Xiaobing Yang. Study of Over-Sampling Method Based on Feature Selection[J]. Telecommunications Science, 2012, 28(1): 91-95.

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References 20

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	被分为正类	被分为负类
实际为正类	TP	FP
实际为负类	FN	TN

数据集	实验样本数（个）		训练集		测试集		特征数（个）
数据集	实验样本数（个）	正类	负类	正类		负类	特征数（个）
Leukemia	72	11	27	14		20	7 129
C olon	62	6	1	6		9	2 000
SRBCT	63	15	28	5		10	2 308
Sonar	178	36	84	11		27	60
Breast Cancer	683	187	326	52		18	10
Satimage	5 104	781	2 323	461		1 539	36
ushrooms	6 208	1 500	3 156	500		052	112
Protein	7 766	3 128	9 647	1 375		216	357

数据集	精确度	FS-Sampling		SMOTE
数据集	精确度	精确度	F-Value	精确度	F-Value
Leukemia	0.888	0.875	0.831	0.847	0.649
Colon	0.86	0.895	0.835	0.895	0.835
SRBCT	1	1	1	0.982	0.893
Sonar	0.843	0.856	0.839	0.829	0.813
Breast Cancer	0.976	0.971	0.97	0.976	0.958
Satimage	0.852	0.863	0.828	0.844	0.795
Mushrooms	0.993	0.989	0.94	0.991	0.938
Protein	0.882	0.863	0.759	0.865	0.762

数据集	精确度	FS-Sam pling		SMOTE
数据集	精确度	精确度	F-Value	精确度	F-Value
Leukemia	0.888	0.861	0.840	0.847	0.649
Colon	0.85	0.893	0.843	0.895	0.847
SRBCT	1	1	1	0.985	0.898
Sonar	0.837	0.851	0.828	0.829	0.813
Breast Cancer	.978	0.975	0.97	0.979	0.958
Satimage	0.852	.861	0.828	0.859	0.795
Mushrooms	0.995	.991	0.943	0.988	0.936
Protern	0.852	0.843	0.759	0.865	0.788

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Study of Over-Sampling Method Based on Feature Selection

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