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Pregled bibliografske jedinice broj: 1515

Preprocessing by cost-sensitive literal reduction algorithm: Reduce


Lavrač, Nada; Gamberger, Dragan; Turney, Peter
Preprocessing by cost-sensitive literal reduction algorithm: Reduce // Learning, Networks and Statistics / Della Riccia, G ; Lenz, H.J ; Kruse, R. (ur.).
Wien; New York: Springer, 1996. str. 179-196


Naslov
Preprocessing by cost-sensitive literal reduction algorithm: Reduce

Autori
Lavrač, Nada ; Gamberger, Dragan ; Turney, Peter

Vrsta, podvrsta i kategorija rada
Poglavlja u knjigama, znanstveni

Knjiga
Learning, Networks and Statistics

Urednik/ci
Della Riccia, G ; Lenz, H.J ; Kruse, R.

Izdavač
Springer

Grad
Wien; New York

Godina
1996

Raspon stranica
179-196

Ključne riječi
Machine learning, literals, genetic algorithm

Sažetak
This study is concerned with whether it is possible to detect what information contained in the training data and background knowledge is relevant for solving the learning problem, and whether irrelevant information can be eliminated in preprocessing before starting the learning process. A case study of data preprocessing for a hybrid genetic algorithm shows that the elimination of irrelevant features can substantially improve the efficiency of learning. In addition, cost-sensitive feature elimination can be effective for reducing costs of induced hypotheses.

Izvorni jezik
Engleski

Znanstvena područja
Elektrotehnika



POVEZANOST RADA


Projekt / tema
00980501

Ustanove
Institut "Ruđer Bošković", Zagreb

Autor s matičnim brojem:
Dragan Gamberger, (13026)