Introduction to statistical pattern recognition (2nd ed.)
Introduction to statistical pattern recognition (2nd ed.)
Eigenfaces vs. Fisherfaces: Recognition Using Class Specific Linear Projection
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Tutorial on Support Vector Machines for Pattern Recognition
Data Mining and Knowledge Discovery
SIAM Journal on Matrix Analysis and Applications
Feature extraction via generalized uncorrelated linear discriminant analysis
ICML '04 Proceedings of the twenty-first international conference on Machine learning
An optimization criterion for generalized discriminant analysis on undersampled problems
IEEE Transactions on Pattern Analysis and Machine Intelligence
A comparison of methods for multiclass support vector machines
IEEE Transactions on Neural Networks
Orthogonal Neighborhood Preserving Projections
ICDM '05 Proceedings of the Fifth IEEE International Conference on Data Mining
Null space versus orthogonal linear discriminant analysis
ICML '06 Proceedings of the 23rd international conference on Machine learning
Regularized discriminant analysis for high dimensional, low sample size data
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
Computational and Theoretical Analysis of Null Space and Orthogonal Linear Discriminant Analysis
The Journal of Machine Learning Research
Multiclass classifiers based on dimension reduction with generalized LDA
Pattern Recognition
Data-Dependent Kernel Machines for Microarray Data Classification
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
Gene Selection for Microarray Data by a LDA-Based Genetic Algorithm
PRIB '08 Proceedings of the Third IAPR International Conference on Pattern Recognition in Bioinformatics
Discriminant Analysis Methods for Microarray Data Classification
AI '08 Proceedings of the 21st Australasian Joint Conference on Artificial Intelligence: Advances in Artificial Intelligence
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Laplacian Linear Discriminant Analysis Approach to Unsupervised Feature Selection
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
Cross-platform microarray data integration using the Normalised Linear Transform
International Journal of Data Mining and Bioinformatics
ISBRA'07 Proceedings of the 3rd international conference on Bioinformatics research and applications
LIBGS: A MATLAB software package for gene selection
International Journal of Data Mining and Bioinformatics
ICIC'10 Proceedings of the 6th international conference on Advanced intelligent computing theories and applications: intelligent computing
Artificial Intelligence in Medicine
A survey of multilinear subspace learning for tensor data
Pattern Recognition
A New and Fast Orthogonal Linear Discriminant Analysis on Undersampled Problems
SIAM Journal on Scientific Computing
A new combined filter-wrapper framework for gene subset selection with specialized genetic operators
MCPR'10 Proceedings of the 2nd Mexican conference on Pattern recognition: Advances in pattern recognition
Fast Kernel Discriminant Analysis for Classification of Liver Cancer Mass Spectra
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
Stable Gene Selection from Microarray Data via Sample Weighting
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
Diversified SVM ensembles for large data sets
ECML'06 Proceedings of the 17th European conference on Machine Learning
ICIC'11 Proceedings of the 7th international conference on Intelligent Computing: bio-inspired computing and applications
Optimal regularization parameter estimation for regularized discriminant analysis
ICIC'11 Proceedings of the 7th international conference on Advanced Intelligent Computing
PAC learnability of rough hypercuboid classifier
ICIC'12 Proceedings of the 8th international conference on Intelligent Computing Theories and Applications
sEMG-Based control of an exoskeleton robot arm
ICIRA'12 Proceedings of the 5th international conference on Intelligent Robotics and Applications - Volume Part II
Selection of interdependent genes via dynamic relevance analysis for cancer diagnosis
Journal of Biomedical Informatics
ICIC'13 Proceedings of the 9th international conference on Intelligent Computing Theories and Technology
A Rayleigh-Ritz style method for large-scale discriminant analysis
Pattern Recognition
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The classification of tissue samples based on gene expression data is an important problem in medical diagnosis of diseases such as cancer. In gene expression data, the number of genes is usually very high (in the thousands) compared to the number of data samples (in the tens or low hundreds); that is, the data dimension is large compared to the number of data points (such data is said to be undersampled). To cope with performance and accuracy problems associated with high dimensionality, it is commonplace to apply a preprocessing step that transforms the data to a space of significantly lower dimension with limited loss of the information present in the original data. Linear Discriminant Analysis (LDA) is a well-known technique for dimension reduction and feature extraction, but it is not applicable for undersampled data due to singularity problems associated with the matrices in the underlying representation. This paper presents a dimension reduction and feature extraction scheme, called Uncorrelated Linear Discriminant Analysis (ULDA), for undersampled problems and illustrates its utility on gene expression data. ULDA employs the Generalized Singular Value Decomposition method to handle undersampled data and the features that it produces in the transformed space are uncorrelated, which makes it attractive for gene expression data. The properties of ULDA are established rigorously and extensive experimental results on gene expression data are presented to illustrate its effectiveness in classifying tissue samples. These results provide a comparative study of various state-of-the-art classification methods on well-known gene expression data sets.