An expert system to classify microarray gene expression data using gene selection by decision tree

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Please use this identifier to cite or link to this item: http://ir.lib.ncu.edu.tw/handle/987654321/29102

Title:	An expert system to classify microarray gene expression data using gene selection by decision tree
Authors:	Horng,JT;Wu,LC;Liu,BJ;Kuo,JL;Kuo,WH;Zhang,JJ
Contributors:	資訊工程研究所
Keywords:	METASTATIC BREAST-CANCER;MOLECULAR CLASSIFICATION;BAYESIAN MODEL;TRASTUZUMAB;INFORMATION;MULTICLASS;PREDICTION;DISCOVERY;DATABASES;DISEASE
Date:	2009
Issue Date:	2010-06-29 20:13:47 (UTC+8)
Publisher:	中央大學
Abstract:	Gene selection call help the analysis of microarray gene expression data. However, it is very difficult to obtain a satisfactory classification result by machine learning techniques because of both the curse-of-dimensionality problem and the over-fitting problem. That is, the dimensions of the features are too large but the samples are too few. In this study, we designed an approach that attempts to avoid these two problems and then used it to select a small set of significant biomarker genes for diagnosis. Finally, we attempted to use these markers for the classification of cancer. This approach was tested the approach on a number of microarray datasets in order to demonstrate that it performs well and is both useful and reliable. (C) 2008 Elsevier Ltd. All rights reserved.
Relation:	EXPERT SYSTEMS WITH APPLICATIONS
Appears in Collections:	[Graduate Institute of Computer Science and Information Engineering] journal & Dissertation

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