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ICPR
2006
IEEE
14 years 11 months ago
Non-Iterative Two-Dimensional Linear Discriminant Analysis
Linear discriminant analysis (LDA) is a well-known scheme for feature extraction and dimensionality reduction of labeled data in a vector space. Recently, LDA has been extended to...
Kohei Inoue, Kiichi Urahama
BMCBI
2007
112views more  BMCBI 2007»
13 years 10 months ago
Selecting dissimilar genes for multi-class classification, an application in cancer subtyping
Background: Gene expression microarray is a powerful technology for genetic profiling diseases and their associated treatments. Such a process involves a key step of biomarker ide...
Zhipeng Cai, Randy Goebel, Mohammad R. Salavatipou...
CAIP
2005
Springer
121views Image Analysis» more  CAIP 2005»
14 years 3 months ago
Feature Space Reduction for Face Recognition with Dual Linear Discriminant Analysis
Linear Discriminant Analysis (LDA) is widely known feature extraction technique that aims at creating a feature set of enhanced discriminatory power. It was addressed by many resea...
Krzysztof Kucharski, Wladyslaw Skarbek, Miroslaw B...
WCE
2007
13 years 11 months ago
Performance Modelling of the Computational Hardware: A Statistical Approach
—This paper proposes and uses multivariate methods as a tool to evaluate performances of the hardware of microcomputers using their performance data, speed and price. The evaluat...
Ibrahim Akman, Yasar Yesilcay
ICASSP
2009
IEEE
14 years 4 months ago
Microarray classification using block diagonal linear discriminant analysis with embedded feature selection
In this paper, block diagonal linear discriminant analysis (BDLDA) is improved and applied to gene expression data. BDLDA is a classification tool with embedded feature selection...
Lingyan Sheng, Roger Pique-Regi, Shahab Asgharzade...