Efficient Gene Expression Analysis by Linking Multiple Data Mining Algorithms (CROSBI ID 507978)
Prilog sa skupa u zborniku | izvorni znanstveni rad | međunarodna recenzija
Podaci o odgovornosti
Bogunović, Nikola ; Marohnić, Viktor ; Debeljak, Željko
engleski
Efficient Gene Expression Analysis by Linking Multiple Data Mining Algorithms
The set of gene micro-arrays, which consists of two leukemia types, was used as a target to evaluate the efficiency of novel integrated data mining classification process. Discovering the most relevant subset of genes among few housands of analyzed genes is necessary to get accurate disease classification. Dimensional complexity of the classification process was reduced by a filter based on mutual information feature selection coupled with the support vector machines classifier in the leave-one-out loop. The result was an efficient and reliable tool named MIFS/SVM hybrid. Optimal procedure parameters that enable accurate classification and attribute selection could be determined within an acceptable time frame.
data mining ; gene expression ; mutual information
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Podaci o prilogu
1-4.
2005.
objavljeno
Podaci o matičnoj publikaciji
Proceedings of the 27th Annual International Conference of the IEEE-EMBS 2005
Zhang, Y.T.
Singapur : London : München : Ženeva : Tokyo : Hong Kong : Taipei : Peking : Šangaj : Tianjin : Chennai: Institute of Electrical and Electronics Engineers (IEEE)
Podaci o skupu
Annual International Conference of the IEEE-EMBS (27 ; 2005)
poster
01.09.2005-04.09.2005
Šangaj, Kina