Naslov
Mutual Information Based Reduction of Data Mining Dimensionality in Gene Expression Analysis

Autori
Marohnić, Viktor ; Debeljak, Željko ; Bogunović, Nikola

Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni

Izvornik
Proceedings of the 26th International Conference on Information Technology Interfaces : ITI 2004 / Lužar Stiffler, Vesna ; Hljuz Dobrić, Vesna - Zagreb : Sveučilišni računski centar Sveučilišta u Zagrebu (Srce), 2004, 249-254

Skup
International Conference on Information Technology Interfaces (26 ; 2004)

Mjesto i datum
Cavtat, Hrvatska, 07.06.2004. - 10.06.2004

Vrsta sudjelovanja
Predavanje

Vrsta recenzije
Međunarodna recenzija

Ključne riječi
data mining ; gene expression ; mutual information

Sažetak
This article introduces a novel method for reducing dimensional complexity of classification problems which are frequently present in gene microarray analysis. Revealing the most relevant subset of genes among few thousands of analyzed genes is necessary to get accurate disease classification. Attribute (gene) filter was developed for such a purpose. The filter, first introduced as Mutual Information Feature Selection (MIFS) was coupled with the support vector machines (SVM) classifier in the leave-one-out (LOO) loop, which resulted in an efficient and reliable tool named MIFS/SVM hybrid. The set of gene microarrays, which consists of two leukemia types, was used as a benchmark. The particular set was thoroughly analyzed by others. Hence it was appropriate to use it for testing the accuracy of MIFS/SVM hybrid based filter.

Izvorni jezik
Engleski

Znanstvena područja
Računarstvo

POVEZANOST RADA