DocumentCode
3114862
Title
Dimensionality Reduction in Gene Expression Database through the Random Projection Method
Author
Borges, Helyane Bronoski ; Nievola, Julio Cesar
Author_Institution
UTFPR-Univ. Tecnol. Fed. do Parana, Ponta Grossa, Brazil
fYear
2009
fDate
13-15 Dec. 2009
Firstpage
557
Lastpage
562
Abstract
Dimensionality reduction applied to gene expression is challenging for machine learning algorithms due to a small number of samples and a high number of attributes. This paper proposes a preprocessing phase by means of random projection method in microarray data. Experimental results are promising and it shows that the use of this method improves the performance of classification algorithms.
Keywords
biology computing; database management systems; genetics; learning (artificial intelligence); pattern classification; classification algorithms; dimensionality reduction; gene expression database; machine learning; microarray data; random projection method; Classification algorithms; Clustering algorithms; Costs; Data mining; Databases; Gene expression; Machine learning; Machine learning algorithms; Stability; Testing;
fLanguage
English
Publisher
ieee
Conference_Titel
Machine Learning and Applications, 2009. ICMLA '09. International Conference on
Conference_Location
Miami Beach, FL
Print_ISBN
978-0-7695-3926-3
Type
conf
DOI
10.1109/ICMLA.2009.84
Filename
5381415
Link To Document