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Feature Selection with Targeted Projection Pursuit

Lookup NU author(s): Dr Amir Enshaei

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Abstract

-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.


Publication metadata

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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