燕山大学学报Issue(2)：153-158,6.DOI:10.3969/j.issn.1007-791X.2013.02.012
偏置判别SVM预测microRNA靶基因
Prediction of microRNA target genes based on biased discriminant SVM
张洪礼 1赵培培 1王常武 1王宝文 1刘文远1
作者信息
- 1. 燕山大学 信息科学与工程学院，河北 秦皇岛 066004
- 折叠
摘要
Abstract
For the data imbalance problem of miRNA target, a target prediction algorithm, Biased Discriminant Support Vector Machine, is proposed to solve the lower prediction accuracy of positive samples. The high-quality data sets and the optimal feature set are selected as the input data. Biased discriminate analysis criteria is selected as the kernel optimize objective function in the empirical feature space, and the conformal transformation of a kernel is adopted to gradually optimize the kernel matrix. Then, the SVM classifier with the optimal kernel matrix is constructed to solve the problem for the prediction causing by imbalance data. Through comparison with the analysis of the experimental results, the biased discriminant support vector machine method shows higher specificity, sensitivity and prediction accuracy, which proves that it has stronger generalization ability and better robustness.关键词
miRNA/靶基因预测/偏置判别SVM/数据不平衡/核优化Key words
miRNA/target prediction/biased discriminant SVM/data imbalance/kernel optimize分类
信息技术与安全科学引用本文复制引用
张洪礼,赵培培,王常武,王宝文,刘文远..偏置判别SVM预测microRNA靶基因[J].燕山大学学报,2013,(2):153-158,6.
