array(2) { ["lab"]=> string(4) "1409" ["publication"]=> string(5) "12619" } Novel regularization method for biomarker selection and cancer classification - Liang Yong | LabXing

Liang Yong

简介 中藥質量控制資訊系統，生物資訊學

大学 Macau University of Science and Technology / Faculty of Information Technology
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Novel regularization method for biomarker selection and cancer classification

2019
期刊 IEEE/ACM transactions on computational biology and bioinformatics
Variable selection has attracted more attention in big data and machine learning fields. In high dimensional data analysis, many relevant variables or variable groups are widely found. For example, people pay more interests to biological pathway or regulatory network in microarray gene expression data. In recent years, regularization methods are commonly used approaches for variable selection. Existing regularization methods generally use L2 penalty to evaluate the grouping effect and Lq(0

  • 卷 17
  • 期 4
  • 页码 1329-1340
  • IEEE
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