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Lookup NU author(s): Dr Amir EnshaeiORCiD
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-The selection of attributes becomes more important, but also more difficult, as the size and dimensionality of data sets grows, particularly in bioinformatics. Targeted Projection Pursuit is a dimension reduction technique previously applied to visualising high-dimensional data; here it is applied to the problem of feature selection. The technique avoids searching the powerset of possible feature combinations by using perceptron learning and attraction-repulsion algorithms to find projections that separate classes in the data. The technique is tested on a range of gene expression data sets. It is found that the classification generalisation performance of the features selected by TPP compares well with standard wrapper and filter approaches, the selection of features generalises more robustly than either, and its time efficiency scales to larger numbers of attributes better than standard searches.
Author(s): Enshaei A, Faith J
Publication type: Article
Publication status: Published
Journal: International Journal of Information Technology and Computer Science
Year: 2015
Volume: 7
Issue: 5
Pages: 34-39
Print publication date: 08/04/2015
ISSN (print): 2074-9007
ISSN (electronic): 2074-9015
Publisher: Modern Education and Computer Science Publisher
URL: http://dx.doi.org/10.5815/ijitcs.2015.05.05
DOI: 10.5815/ijitcs.2015.05.05
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