Pregled bibliografske jedinice broj: 982710
Utilising Filter Inferred Information in Nature- inspired Hybrid Feature Selection
Utilising Filter Inferred Information in Nature- inspired Hybrid Feature Selection // Proceedings of the 3rd International Conference on Smart Systems and Technologies (SST 2018) / Žagar, Drago ; Martinović, Goran ; Rimac Drlje, Snježana ; Miličević, Kruno (ur.).
Osijek: Fakultet elektrotehnike, računarstva i informacijskih tehnologija Sveučilišta Josipa Jurja Strossmayera u Osijeku, 2018. str. 117-123 doi:10.1109/SST.2018.8564720 (predavanje, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)
CROSBI ID: 982710 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
Naslov
Utilising Filter Inferred Information in Nature- inspired Hybrid Feature Selection
Autori
Zorić, Bruno ; Bajer, Dražen ; Martinović, Goran
Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni
Izvornik
Proceedings of the 3rd International Conference on Smart Systems and Technologies (SST 2018)
/ Žagar, Drago ; Martinović, Goran ; Rimac Drlje, Snježana ; Miličević, Kruno - Osijek : Fakultet elektrotehnike, računarstva i informacijskih tehnologija Sveučilišta Josipa Jurja Strossmayera u Osijeku, 2018, 117-123
ISBN
978-1-5386-7189-4
Skup
International Conference on Smart Systems and Technologies 2018 (SST 2018)
Mjesto i datum
Osijek, Hrvatska, 10.10.2018. - 12.10.2018
Vrsta sudjelovanja
Predavanje
Vrsta recenzije
Međunarodna recenzija
Ključne riječi
nature-inspired algorithms , feature selection , filter , hybrid , wrapper
Sažetak
The development of modern smart systems such as smart grid, medical diagnosis assessment tools or quality control systems in manufacturing relies heavily on data and knowledge attained from, possibly, large amounts of information. Several well known but hard to solve problems often arise during this process, a prominent one being the problem of high dimensionality. Although different methods of feature selection are both proposed and employed in order to ameliorate its effects, it remains an open problem. Recently, hybrid procedures combining both filters as a preprocessing step and a wrapper as a refining step have proven to be an effective approach. Along the problem of filter and wrapper selection, the problem of incorporating knowledge inferred by the filter into the wrapper is an interesting one. In this paper, a novel approach is proposed that relies on filter information in order to generate the initial population of a nature-inspired algorithm utilised as the wrapper. Promising results were obtained on several real-world datasets that demonstrate the effectiveness of the proposed approach both in terms of classification quality and dimensionality reduction. Results of the statistical analysis of performance when compared with other approaches further emphasize the observed benefits.
Izvorni jezik
Engleski
Znanstvena područja
Računarstvo
POVEZANOST RADA
Projekti:
KK.01.1.1.01.0009 - Napredne metode i tehnologije u znanosti o podatcima i kooperativnim sustavima (EK )
Ustanove:
Fakultet elektrotehnike, računarstva i informacijskih tehnologija Osijek