Impact of Antibody Panel Size on Classification Accuracy
2011
Inese Poļaka, Arkādijs Borisovs

This paper experimentally studies the influence of antibody panel size reduction on classification results. The presented study includes four classification methods and five feature evaluators that are applied to five different biomedical data sets with large dimensionality (1200 features). The behaviour of the classifiers in these data sets is examined to reveal overall trends of dimensionality reduction impact on classification accuracy.


Keywords
bioinformatics, classification accuracy, dimensionality reduction, feature selection
DOI
10.2478/v10143-011-0047-9
Hyperlink
http://www.degruyter.com/view/j/acss.2011.45.issue--1/v10143-011-0047-9/v10143-011-0047-9.xml?format=INT

Poļaka, I., Borisovs, A. Impact of Antibody Panel Size on Classification Accuracy. IT and Management Science. Vol.49, 2011, pp.85-90. ISSN 1407-7493. Available from: doi:10.2478/v10143-011-0047-9

Publication language
English (en)
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