文章基本信息

标题：The Impact of Feature Selection on the Information Held in Bioinformatics Data
作者：Madara Gasparovica-Asite ; Inese Polaka ; Ludmila Alekseyeva 等
期刊名称：Information Technology and Management Science
印刷版ISSN：2255-9086
电子版ISSN：2255-9094
出版年度：2015
卷号：18
期号：1
页码：115-121
DOI：10.1515/itms-2015-0018
语种：English
出版社：Walter de Gruyter GmbH
摘要：The present research examines a wide range of attribute selection methods – 86 methods that include both ranking and subset evaluation approaches. The efficacy evaluation of these methods is carried out using bioinformatics data sets provided by the Latvian Biomedical Research and Study Centre. The data sets are intended for diagnostic task purposes and incorporate values of more than 1000 proteomics features as well as diagnosis (specific cancer or healthy) determined by a golden standard method (biopsy and histological analysis). The diagnostic task is solved using classification algorithms FURIA, RIPPER, C4.5, CART, KNN, SVM, FB+ and GARF in the initial and various sets with reduced dimensionality. The research paper finalises with conclusions about the most effective methods of attribute subset selection for classification task in diagnostic proteomics data.
关键词：Bioinformatics ; classification ; data mining ; diagnostics ; feature selection