文章基本信息

标题：INTEGRATED FRAMEWORK OF FEATURE SELECTION FROM MICROARRAY DATA FOR CLASSIFICATION
本地全文：下载
作者：AHMED A. ABDULWAHHAB ; MAKHFUDZAH MOKHTAR (Dr. ; M. IQBAL B. SARIPAN (Assoc. Prof Dr. 等
期刊名称：Journal of Theoretical and Applied Information Technology
印刷版ISSN：1992-8645
电子版ISSN：1817-3195
出版年度：2015
卷号：73
期号：2
出版社：Journal of Theoretical and Applied
摘要：A DNA microarray has the ability to record levels of huge number of genes in one experiment. Previous research has shown that this technology can be helpful in the classification of cancers and their treatments outcomes. Normally, cancer microarray data has a limited number of samples which have a tremendous amount of genes expression levels as features. To specify relevant genes participated in different kinds of cancer still represents a challenge. For the purpose of extracting useful genes information from the data of cancer microarray, gene selection algorithms were examined systematically in this study and an integrated framework of gene selection was proposed. Using feature ranking based on absolute value two sample t-test with pooled variance estimate evaluation criterion combined with sequential forward feature selection, we show that the performance of classification at least as better as published results can be obtained on the therapy outcomes regarding breast cancer patients. Also, we reveal that combined use of different feature selection and classification approaches makes it feasible to select strongly relevant genes with high confidence.
关键词：Microarray; Gene Selection; Classification; Feature Ranking; Sequential Forward Feature Selection; Breast Cancer; Leukemia.