Comparison of Filter Techniques for Two-Step Feature Selection
Peter Drotár; Department of Computers and Informatics, Technical University of Košice, Letná 9, Košice ; Slavomír Šimoňák; Department of Computers and Informatics, Technical University of Košice ; Emília Pietriková; Department of Computers and Informatics, Technical University of Košice ; Martin Chovanec; Department of Computers and Informatics, Technical University of Košice ; Eva Chovancová; Department of Computers and Informatics, Technical University of Košice ; Norbert Ádám; Department of Computers and Informatics, Technical University of Košice ; Csaba Szabó; Department of Computers and Informatics, Technical University of Košice ; Anton Baláž; Department of Computers and Informatics, Technical University of Košice ; Miroslav Biňas; Department of Computers and Informatics, Technical University of Košice
Computing and Informatics, Tome 35 (2017) no. 4, / Harvested from Computing and Informatics
Text on Computing and Informatics
In the last decade, the processing of the high dimensional data became inevitable task in many areas of research and daily life. Feature selection (FS), as part of the data processing methodology, is an important step in knowledge discovery. This paper proposes nine variation of two-step feature selection approach with filter FS employed in the first step and exhaustive search in the second step. The performance of the proposed methods is comparatively analysed from the stability and predictive performance point of view. As the obtained results indicate the choice of the filter FS in the first stage has strong influence on the resulting stability. Here, the choice of univariate Pearson correlation coefficient based FS method appears to provide the most stable results.
Publié le : 2017-07-06
Classification:  Knowledge and Information Engineering,  Feature selection, selection stability, high dimensionality, exhaustive search, bioinformatics 
@article{cai2017_3_597,
     author = {Peter Drot\'ar; Department of Computers and Informatics, Technical University of Ko\v sice, Letn\'a 9, Ko\v sice and Slavom\'\i r \v Simo\v n\'ak; Department of Computers and Informatics, Technical University of Ko\v sice and Em\'\i lia Pietrikov\'a; Department of Computers and Informatics, Technical University of Ko\v sice and Martin Chovanec; Department of Computers and Informatics, Technical University of Ko\v sice and Eva Chovancov\'a; Department of Computers and Informatics, Technical University of Ko\v sice and Norbert \'Ad\'am; Department of Computers and Informatics, Technical University of Ko\v sice and Csaba Szab\'o; Department of Computers and Informatics, Technical University of Ko\v sice and Anton Bal\'a\v z; Department of Computers and Informatics, Technical University of Ko\v sice and Miroslav Bi\v nas; Department of Computers and Informatics, Technical University of Ko\v sice},
     title = {Comparison of Filter Techniques for Two-Step Feature Selection},
     journal = {Computing and Informatics},
     volume = {35},
     number = {4},
     year = {2017},
     language = {en},
     url = {http://dml.mathdoc.fr/item/cai2017_3_597}
}

Peter Drotár; Department of Computers and Informatics, Technical University of Košice, Letná 9, Košice; Slavomír Šimoňák; Department of Computers and Informatics, Technical University of Košice; Emília Pietriková; Department of Computers and Informatics, Technical University of Košice; Martin Chovanec; Department of Computers and Informatics, Technical University of Košice; Eva Chovancová; Department of Computers and Informatics, Technical University of Košice; Norbert Ádám; Department of Computers and Informatics, Technical University of Košice; Csaba Szabó; Department of Computers and Informatics, Technical University of Košice; Anton Baláž; Department of Computers and Informatics, Technical University of Košice; Miroslav Biňas; Department of Computers and Informatics, Technical University of Košice. Comparison of Filter Techniques for Two-Step Feature Selection. Computing and Informatics, Tome 35 (2017) no. 4, . http://gdmltest.u-ga.fr/item/cai2017_3_597/