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基于层级规则树的跨平台基因表达数据分类
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  • 英文篇名:Cross-platform Gene Expression Data Classification Based on Hierarchical Rule Tree
  • 作者:蔡瑞初 ; 侯永杰 ; 郝志峰
  • 英文作者:CAI Ruichu;HOU Yongjie;HAO Zhifeng;School of Computers,Guangdong University of Technology;School of Mathematics and Big Data,Foshan University;
  • 关键词:数据分类 ; 跨平台 ; 规则学习 ; 特征选择 ; 基因表达数据
  • 英文关键词:data classification;;cross-platform;;rule learning;;feature selection;;gene expression data
  • 中文刊名:JSJC
  • 英文刊名:Computer Engineering
  • 机构:广东工业大学计算机学院;佛山科学技术学院数学与大数据学院;
  • 出版日期:2018-08-29 16:35
  • 出版单位:计算机工程
  • 年:2019
  • 期:v.45;No.502
  • 基金:国家自然科学基金(61472089);; NSFC-广东联合基金(U1501254);; 广东省自然科学基金(2014A030306004,2014A030308008);; 广东省科技计划项目(2015B010108006,2015B010131015);; 广东特支计划(2015TQ01X140);; 广州市科技计划项目(201604016075);; 广州市珠江科技新星专项(201610010101)
  • 语种:中文;
  • 页:JSJC201907005
  • 页数:6
  • CN:07
  • ISSN:31-1289/TP
  • 分类号:32-37
摘要
基因检测技术运用至今已积累大量来自不同平台的数据,针对传统数据分类模式难以在不同平台间进行有效迁移的问题,提出一种基于层级规则树的基因表达数据分类算法k-HRT。设计数据转换与规则预筛选策略,实现算法的快速挖掘,以解决由跨平台特性所带来的大规模数据问题。在真实基因表达数据集上的实验结果表明,相对k-TSP算法、SVM-RFE算法,k-HRT算法能够有效提高分类精度。
        The application of genetic testing technology has accumulated a large amount of data from different platforms.To address the problem that it is difficult to migrate traditional data classification modes across different platforms,this paper proposes a gene expression data classification algorithm k-HRT based on Hierarchy Rule Tree(HRT).The strategy of data conversion and rule pre-screening is designed to realize the fast mining of the algorithm to solve the large-scale data problems caused by cross-platform characteristics.Experimental results on real gene expression datasets show that,compared with k-TSP algorithm and SVM-RFE algorithm,k-HRT algorithm can effectively improve classification accuracy.
引文
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