The Impact of Feature Selection on the Information Held in Bioinformatics Data

Information Technology and Management Science

Gasparovica-Asite Madara¹  Alekseyeva Ludmila¹  Polaka Inese¹ 

[1] Riga Technical University;

关键词: Bioinformatics;    classification;    data mining;    diagnostics;    feature selection;   

DOI  :  10.1515/itms-2015-0018

来源: DOAJ

【 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.

【 授权许可】

Unknown