IDR/QR: an incremental dimension reduction algorithm via QR decomposition
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
Using Uncorrelated Discriminant Analysis for Tissue Classification with Gene Expression Data
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
A Two-Stage Linear Discriminant Analysis via QR-Decomposition
IEEE Transactions on Pattern Analysis and Machine Intelligence
IDR/QR: An Incremental Dimension Reduction Algorithm via QR Decomposition
IEEE Transactions on Knowledge and Data Engineering
IEEE Transactions on Pattern Analysis and Machine Intelligence
Null space versus orthogonal linear discriminant analysis
ICML '06 Proceedings of the 23rd international conference on Machine learning
Discriminant feature extraction using dual-objective optimization model
Pattern Recognition Letters
Data complexity assessment in undersampled classification of high-dimensional biomedical data
Pattern Recognition Letters
Feature Reduction via Generalized Uncorrelated Linear Discriminant Analysis
IEEE Transactions on Knowledge and Data Engineering
Graph Embedding and Extensions: A General Framework for Dimensionality Reduction
IEEE Transactions on Pattern Analysis and Machine Intelligence
The theoretical analysis of GLRAM and its applications
Pattern Recognition
Face recognition using a kernel fractional-step discriminant analysis algorithm
Pattern Recognition
Two-stage optimal component analysis
Computer Vision and Image Understanding
Solution for supervised graph embedding: A case study
Signal Processing
Feature extraction using constrained maximum variance mapping
Pattern Recognition
Locally linear discriminant embedding: An efficient method for face recognition
Pattern Recognition
On Applying Dimension Reduction for Multi-labeled Problems
MLDM '07 Proceedings of the 5th international conference on Machine Learning and Data Mining in Pattern Recognition
General Solution for Supervised Graph Embedding
ECML '07 Proceedings of the 18th European conference on Machine Learning
A note on two-dimensional linear discriminant analysis
Pattern Recognition Letters
A Hybrid Nonlinear-Discriminant Analysis Feature Projection Technique
AI '08 Proceedings of the 21st Australasian Joint Conference on Artificial Intelligence: Advances in Artificial Intelligence
Fast algorithm for updating the discriminant vectors of dual-space LDA
IEEE Transactions on Information Forensics and Security
Ubiquitously supervised subspace learning
IEEE Transactions on Image Processing
A new and fast implementation for null space based linear discriminant analysis
Pattern Recognition
Generalized discriminant analysis: a matrix exponential approach
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Dimension reduction by a novel unified scheme using divergence analysis and genetic search
Digital Signal Processing
Diagnosis of liver diseases from P31 MRS data based on feature selection using genetic algorithm
LSMS/ICSEE'10 Proceedings of the 2010 international conference on Life system modeling and simulation and intelligent computing, and 2010 international conference on Intelligent computing for sustainable energy and environment: Part III
Linear projection methods in face recognition under unconstrained illuminations: a comparative study
CVPR'04 Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition
Uncorrelated trace ratio linear discriminant analysis for undersampled problems
Pattern Recognition Letters
Fast Algorithms for the Generalized Foley-Sammon Discriminant Analysis
SIAM Journal on Matrix Analysis and Applications
A New and Fast Orthogonal Linear Discriminant Analysis on Undersampled Problems
SIAM Journal on Scientific Computing
Orthogonal Complete Discriminant Locality Preserving Projections for Face Recognition
Neural Processing Letters
An optimization criterion for generalized marginal Fisher analysis on undersampled problems
International Journal of Automation and Computing
Face recognition based on the multi-scale local image structures
Pattern Recognition
Computers and Electrical Engineering
Weighted generalized kernel discriminant analysis using fuzzy memberships
WSEAS Transactions on Mathematics
Kernel uncorrelated discriminant analysis for radar target recognition
ICONIP'06 Proceedings of the 13th international conference on Neural Information Processing - Volume Part II
Face recognition by inverse fisher discriminant features
ICB'06 Proceedings of the 2006 international conference on Advances in Biometrics
Recent advances in subspace analysis for face recognition
SINOBIOMETRICS'04 Proceedings of the 5th Chinese conference on Advances in Biometric Person Authentication
The solution space for fisher discriminant analysis and the uniqueness under constraints
SINOBIOMETRICS'04 Proceedings of the 5th Chinese conference on Advances in Biometric Person Authentication
Fast calculation for fisher criteria in small sample size problem
SINOBIOMETRICS'04 Proceedings of the 5th Chinese conference on Advances in Biometric Person Authentication
Regularized orthogonal linear discriminant analysis
Pattern Recognition
Incremental complete LDA for face recognition
Pattern Recognition
Trace quotient problems revisited
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part II
Incremental learning of complete linear discriminant analysis for face recognition
Knowledge-Based Systems
Novel Fisher discriminant classifiers
Pattern Recognition
Computational Optimization and Applications
Equivalence Between LDA/QR and Direct LDA
International Journal of Cognitive Informatics and Natural Intelligence
Modular discriminant analysis and its applications
Artificial Intelligence Review
Computers and Electronics in Agriculture
Structure preserving non-negative matrix factorization for dimensionality reduction
Computer Vision and Image Understanding
Development and evaluation of a biomedical search engine using a predicate-based vector space model
Journal of Biomedical Informatics
Hi-index | 0.14 |
An optimization criterion is presented for discriminant analysis. The criterion extends the optimization criteria of the classical Linear Discriminant Analysis (LDA) through the use of the pseudoinverse when the scatter matrices are singular. It is applicable regardless of the relative sizes of the data dimension and sample size, overcoming a limitation of classical LDA. The optimization problem can be solved analytically by applying the Generalized Singular Value Decomposition (GSVD) technique. The pseudoinverse has been suggested and used for undersampled problems in the past, where the data dimension exceeds the number of data points. The criterion proposed in this paper provides a theoretical justification for this procedure. An approximation algorithm for the GSVD-based approach is also presented. It reduces the computational complexity by finding subclusters of each cluster and uses their centroids to capture the structure of each cluster. This reduced problem yields much smaller matrices to which the GSVD can be applied efficiently. Experiments on text data, with up to 7,000 dimensions, show that the approximation algorithm produces results that are close to those produced by the exact algorithm.