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
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;
Conference_Titel :
Machine Learning and Applications, 2009. ICMLA '09. International Conference on
Conference_Location :
Miami Beach, FL
Print_ISBN :
978-0-7695-3926-3
DOI :
10.1109/ICMLA.2009.84
