Introduction to statistical pattern recognition (2nd ed.)
Introduction to statistical pattern recognition (2nd ed.)
Self-organizing maps
Toward Bayes-Optimal Linear Dimension Reduction
IEEE Transactions on Pattern Analysis and Machine Intelligence
Curvilinear component analysis: a self-organizing neural network for nonlinear mapping of data sets
IEEE Transactions on Neural Networks
Bayes-optimality motivated linear and multilayered perceptron-based dimensionality reduction
IEEE Transactions on Neural Networks
Discriminatory mining of gene expression microarray data
Journal of VLSI Signal Processing Systems - Special issue on signal processing and neural networks for bioinformatics
Recent advances in visual and infrared face recognition: a review
Computer Vision and Image Understanding
Improved-LDA based face recognition using both facial global and local information
Pattern Recognition Letters
Face recognition using a kernel fractional-step discriminant analysis algorithm
Pattern Recognition
A Gradient Linear Discriminant Analysis for Small Sample Sized Problem
Neural Processing Letters
Speech feature analysis using step-weighted linear discriminant analysis
ICECS'03 Proceedings of the 2nd WSEAS International Conference on Electronics, Control and Signal Processing
Kernel Weighted Scatter-Difference-Based Discriminant Analysis for Face Recognition
ICIAR '08 Proceedings of the 5th international conference on Image Analysis and Recognition
An efficient classifier to diagnose of schizophrenia based on the EEG signals
Expert Systems with Applications: An International Journal
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Expert Systems with Applications: An International Journal
An Innovative Weighted 2DLDA Approach for Face Recognition
PCM '09 Proceedings of the 10th Pacific Rim Conference on Multimedia: Advances in Multimedia Information Processing
A new and fast implementation for null space based linear discriminant analysis
Pattern Recognition
Linear dimensionality reduction using relevance weighted LDA
Pattern Recognition
SVM decision boundary based discriminative subspace induction
Pattern Recognition
Classification of BMD and ADHD patients using their EEG signals
Expert Systems with Applications: An International Journal
Distance metric learning by minimal distance maximization
Pattern Recognition
A linear discriminant analysis method based on mutual information maximization
Pattern Recognition
A multi-manifold discriminant analysis method for image feature extraction
Pattern Recognition
An Innovative Weighted 2DLDA Approach for Face Recognition
Journal of Signal Processing Systems
Energy Efficient Distributed Face Recognition in Wireless Sensor Network
Wireless Personal Communications: An International Journal
Weighted generalized kernel discriminant analysis using fuzzy memberships
WSEAS Transactions on Mathematics
WSEAS Transactions on Mathematics
Face recognition using uncorrelated, weighted linear discriminant analysis
ICAPR'05 Proceedings of the Third international conference on Pattern Recognition and Image Analysis - Volume Part II
Extending kernel fisher discriminant analysis with the weighted pairwise chernoff criterion
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part IV
A study of applying dimensionality reduction to restrict the size of a hypothesis space
ILP'05 Proceedings of the 15th international conference on Inductive Logic Programming
Feature extraction using fuzzy maximum margin criterion
Neurocomputing
Heteroscedastic linear feature extraction based on sufficiency conditions
Pattern Recognition
Real-time fault detection in manufacturing environments using face recognition techniques
Journal of Intelligent Manufacturing
Maxi-Min discriminant analysis via online learning
Neural Networks
Face recognition by searching most similar sample with immune learning
ICARIS'12 Proceedings of the 11th international conference on Artificial Immune Systems
Incorporating linear discriminant analysis in neural tree for multidimensional splitting
Applied Soft Computing
Generalized mean for feature extraction in one-class classification problems
Pattern Recognition
Two-factor face authentication using matrix permutation transformation and a user password
Information Sciences: an International Journal
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Linear projections for dimensionality reduction, computed using linear discriminant analysis (LDA), are commonly based on optimization of certain separability criteria in the output space. The resulting optimization problem is linear, but these separability criteria are not directly related to the classification accuracy in the output space. Consequently, a trial and error procedure has to be invoked, experimenting with different separability criteria that differ in the weighting function used and selecting the one that performed best on the training set. Often, even the best weighting function among the trial choices results in poor classification of data in the subspace. In this short paper, we introduce the concept of fractional dimensionality and develop an incremental procedure, called the fractional-step LDA (F-LDA) to reduce the dimensionality in fractional steps. The F-LDA algorithm is more robust to the selection of weighting function and for any given weighting function, it finds a subspace in which the classification accuracy is higher than that obtained using LDA.