文章基本信息

标题：Dimension and Complexity Study for Alzheimer’s disease Feature Extraction
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作者：Mohamed M. Dessouky ; Mohamed A. Elrashidy ; Taha E. Taha 等
期刊名称：International Journal of Engineering and Computer Science
印刷版ISSN：2319-7242
出版年度：2014
卷号：3
期号：7
页码：7132-7137
出版社：IJECS
摘要：This paper discusses the problem of dimensionality and computational complexity analysis for feature extraction proposed algorithms of Alzheimer’s disease. The effective features are very useful for some of the discrimations and to assist the physicians in the detection of abnormalities. This paper concern two main issues that must be confronted which are: The first one concern the study of how the classification accuracy depends on the dimensionality (i.e. the number of features). The second issue is the computational complexity of designing the classifier. As the number of features increases, the classification error decreases which consequently improve the accuracy of the classifier
关键词：Diagnosis; Alzheimer’s disease; Computer Aided Diagnosis; Feature Extraction; Dimensionality; Complexity Analysis; Feature reduction; and Support Vector Machine