prikaz prve stranice dokumenta Effects of dataset characteristics on the performance of feature selection techniques
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Effects of dataset characteristics on the performance of feature selection techniques
Applied Soft Computing, 52 (2017); 109-119. https://doi.org/10.1016/j.asoc.2016.12.023
Oreški, Dijana; Oreški, Stjepan; Kliček, Božidar

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Oreški, D., Oreški, S. i Kliček, B. (2017). Effects of dataset characteristics on the performance of feature selection techniques. Applied Soft Computing, 52., 109-119. doi: 10.1016/j.asoc.2016.12.023

Oreški, Dijana, et al. "Effects of dataset characteristics on the performance of feature selection techniques." Applied Soft Computing, vol. 52, 2017, str. 109-119. https://doi.org/10.1016/j.asoc.2016.12.023

Oreški, Dijana, Stjepan Oreški i Božidar Kliček. "Effects of dataset characteristics on the performance of feature selection techniques." Applied Soft Computing 52 (2017): 109-119. https://doi.org/10.1016/j.asoc.2016.12.023

Oreški, D., Oreški, S. i Kliček, B. (2017) 'Effects of dataset characteristics on the performance of feature selection techniques', Applied Soft Computing, 52, str. 109-119. doi: 10.1016/j.asoc.2016.12.023

Oreški D, Oreški S, Kliček B. Effects of dataset characteristics on the performance of feature selection techniques. Applied Soft Computing [Internet]. 03.2017. [pristupljeno 29.11.2024.];52:109-119. doi: 10.1016/j.asoc.2016.12.023

D. Oreški, S. Oreški i B. Kliček, "Effects of dataset characteristics on the performance of feature selection techniques", Applied Soft Computing, vol. 52, str. 109-119, Ožujak 2017. [Online]. Dostupno na: https://urn.nsk.hr/urn:nbn:hr:211:165896. [Citirano: 29.11.2024.]

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Podaci o radu
Naslov (engleski)Effects of dataset characteristics on the performance of feature selection techniques
AutorDijana Oreški
AutorStjepan Oreški
AutorBožidar Kliček
Autorova ustanovaSveučilište u Zagrebu
Fakultet organizacije i informatike
Znanstveno / umjetničko
područje, polje i grana		DRUŠTVENE ZNANOSTI
Informacijske i komunikacijske znanosti
Sažetak (engleski)
While extensive research in data mining has been devoted to developing better feature selection techniques, none of this research has examined the intrinsic relationship between dataset characteristics and a feature selection techniques performance. Thus, our research examines experimentally how dataset characteristics affect both the accuracy and the time complexity of feature selection. To evaluate the performance of various feature selection techniques on datasets of different characteristics, extensive experiments with five feature selection techniques, three types of classification algorithms, seven types of dataset characterization methods and all possible combinations of dataset characteristics are conducted on 128 publicly available datasets. We apply the decision tree method to evaluate the interdependencies between dataset characteristics and performance. The results of the study reveal the intrinsic relationship between dataset characteristics and feature selection techniques performance. Additionally, our study contributes to research in data mining by providing a roadmap for future research on feature selection and a significantly wider framework for comparative analysis. (C) 2016 Elsevier B.V. All rights reserved.
Ključne riječi (engleski)
Jezikengleski
Vrsta publikacijeZnanstveni rad - Izvorni znanstveni rad
Status objaveObjavljen
Vrsta recenzijeRecenziran - međunarodna recenzija
Verzija publikacijeObjavljena verzija rada (izdavačev PDF)
Naslov časopisaApplied Soft Computing
Brojčani podacivol. 52, str. 109-119
p-ISSN1568-4946
e-ISSN1872-9681
DOIhttps://doi.org/10.1016/j.asoc.2016.12.023
URN:NBNurn:nbn:hr:211:165896
Datum objave publikacije2017-03
URL dokumentahttp://www.sciencedirect.com/science/article/pii/S156849461630641X
Vrsta resursaTekst
Prava pristupaZatvoreni pristup
Uvjeti korištenjaIkona licence Zaštićeno autorskim pravom.
Datum i vrijeme pohrane2017-09-19 07:44:59