Pregled bibliografske jedinice broj: 485008
Advances in Class Noise Detection
Advances in Class Noise Detection // Proc. of 19th European Conference on Artificiel Intelligence, ECAI 2010 / Coelho, Helder ; Studer, Rudi ; Wooldridge, Michael (ur.).
Lisabon, Portugal, 2010. str. 1105-1106 (predavanje, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)
CROSBI ID: 485008 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
Naslov
Advances in Class Noise Detection
Autori
Sluban, Borut ; Gamberger, Dragan ; Lavrač, Nada
Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni
Izvornik
Proc. of 19th European Conference on Artificiel Intelligence, ECAI 2010
/ Coelho, Helder ; Studer, Rudi ; Wooldridge, Michael - , 2010, 1105-1106
ISBN
978-1-60750-605-8
Skup
19th European Conference on Artificiel Intelligence, ECAI 2010
Mjesto i datum
Lisabon, Portugal, 16.08.2010. - 20.08.2010
Vrsta sudjelovanja
Predavanje
Vrsta recenzije
Međunarodna recenzija
Ključne riječi
machine learning; noise detection; random forest
Sažetak
Noise filtering is usually used in data preprocessing to improve the accuracy of induced classifiers. Our goal is different: we aim at detecting noisy instances to be inspected by the domain expert in the phase of data understanding. Consequently, our noise detection algorithms should have high precision of class noise detection, where the precision-recall trade-off is modeled using the F-measure. New variants of class noise detection algorithms have been developed, including the high agreement random forest filter which ensures very high precision of identified erroneous data instances.
Izvorni jezik
Engleski
Znanstvena područja
Računarstvo
POVEZANOST RADA
Projekti:
098-0982560-2563 - Algoritmi strojnog učenja i njihova primjena (Gamberger, Dragan, MZOS ) ( CroRIS)
Ustanove:
Institut "Ruđer Bošković", Zagreb
Profili:
Dragan Gamberger
(autor)
