摘要
针对处理肿瘤基因表达数据特征选择问题,提出了一种特征选择方法 LLE Score.该方法是典型的过滤器类型特征选择方法,在样本类别信息的基础上,LLE Score针对特征向量的局部邻域保存能力进行评价,并且根据评价结果进行特征的选取,以此达到良好的特征选择效果.在实验部分对肿瘤数据集进行特征选择,并采用支持向量机分类器计算分类准确率.通过分类准确率说明了该方法的有效性.
To solve the problem of feature selection based on tumor gene expression data, this paper presents a feature selection method called LLE Score. The algorithm is a typical filter feature selection method based on the label information of sample. To achieve good feature selection, LLE Score can evaluate the feature vector according to the capability of saving the local neighborhood, and the featureis selected according to the evaluation results. Tumor gene expressive dataset is used by LLE Score to demonstrate the feasibility. The effectiveness of LLE Score is evaluated by the classification accuracy of support vector machine ( SVM) classifier.
出处
《北京工业大学学报》
CAS
CSCD
北大核心
2015年第8期1145-1150,共6页
Journal of Beijing University of Technology
基金
国家科技重大专项资助项目(2011BAC12B0304)
北京市教育委员会科技计划项目(JC002011200903)