A new regularized least squares support vector regression for gene selection

被引:0
作者
Pei-Chun Chen
Su-Yun Huang
Wei J Chen
Chuhsing K Hsiao
机构
[1] National Taiwan University,Bioinformatics and Biostatistics Core Laboratory
[2] Academia Sinica,Institute of Statistical Science
[3] National Taiwan University,Department of Public Health
[4] National Taiwan University,Institute of Epidemiology
来源
BMC Bioinformatics | / 10卷
关键词
Support Vector Machine; Acute Myeloid Leukemia; Acute Lymphoblastic Leukemia; Support Vector Regression; Gene Selection;
D O I
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中图分类号
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  • [11] Bloomfield CD(2003)Dimensionality reduction via sparse support vector machines Journal of Machine Learning Research 3 1229-840
  • [12] Lander ES(2002)Gene selection for cancer classification using support vector machines Machine Learning 46 389-97
  • [13] Brown MPS(2008)Incremental forward feature selection with application to microarray gene expression data J Biopharm Stat 18 827-819
  • [14] Grundy WN(2005)Feature selection and classification for microarray data analysis: evolutionary methods for identifying predictive genes BMC Bioinformatics 6 148-2402
  • [15] Lin D(2006)Gene selection algorithms for microarray data based on least squares support vector machine BMC Bioinformatics 7 95-78
  • [16] Cristianini N(2003)Gene selection: a Bayesian variable selection approach Bioinformatics 19 90-1270
  • [17] Sugnet CW(2004)Bayesian variable selection in multinomial probit models to identify molecular signatures of disease stage Biometrics 60 812-48
  • [18] Furey TS(2005)Bayesian model average: development of an improved multi-class, gene selection and classification tool for microarray data Bioinformatics 21 2394-1178
  • [19] Manuel Ares J(2006)Multi-class cancer classification using multinomial probit regression with Bayesian gene selection Syst Biol (Stevenage) 153 70-346
  • [20] Haussler D(1994)Flexible discriminant analysis by optimal scoring Journal of the American Statistical Association 89 1255-6750