An analysis of the max-min approach to feature selection and ordering
Pattern Recognition Letters
Floating search methods in feature selection
Pattern Recognition Letters
Divergence Based Feature Selection for Multimodal Class Densities
IEEE Transactions on Pattern Analysis and Machine Intelligence
Feature Selection: Evaluation, Application, and Small Sample Performance
IEEE Transactions on Pattern Analysis and Machine Intelligence
Feature selection toolbox software package
Pattern Recognition Letters - In memory of Professor E.S. Gelsema
A Framework for Classifier Fusion: Is It Still Needed?
Proceedings of the Joint IAPR International Workshops on Advances in Pattern Recognition
Advances in Statistical Feature Selection
ICAPR '01 Proceedings of the Second International Conference on Advances in Pattern Recognition
Feature selection based on a modified fuzzy C-means algorithm with supervision
Information Sciences—Informatics and Computer Science: An International Journal
Toward Integrating Feature Selection Algorithms for Classification and Clustering
IEEE Transactions on Knowledge and Data Engineering
Iterative RELIEF for Feature Weighting: Algorithms, Theories, and Applications
IEEE Transactions on Pattern Analysis and Machine Intelligence
Online Feature Selection Algorithm with Bayesian l 1 Regularization
PAKDD '09 Proceedings of the 13th Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining
KES'07/WIRN'07 Proceedings of the 11th international conference, KES 2007 and XVII Italian workshop on neural networks conference on Knowledge-based intelligent information and engineering systems: Part III
The novel feature selection method based on emotion recognition system
ICIC'06 Proceedings of the 2006 international conference on Computational Intelligence and Bioinformatics - Volume Part III
The interactive feature selection method development for an ANN based emotion recognition system
KES'06 Proceedings of the 10th international conference on Knowledge-Based Intelligent Information and Engineering Systems - Volume Part III
RPCA: a novel preprocessing method for PCA
Advances in Artificial Intelligence
Large Margin Subspace Learning for feature selection
Pattern Recognition
Spatial distance join based feature selection
Engineering Applications of Artificial Intelligence
Joint Laplacian feature weights learning
Pattern Recognition
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The authors present new techniques in the statistical methodology for selecting optimal subsets of features for data representation and classification. They provide guidelines for choosing an approach, depending on the extent of a priori knowledge of the problem. They review two basic approaches and specify the conditions for using those approaches. One approach involves computationally effective floating-search methods. The alternative approach trades off the requirement for a priori information for the requirement of sufficient data to represent the distributions involved. This approach is particularly suitable when the underlying probability distributions are not unimodal. It attempts to achieve simultaneous feature selection and decision-rule inference. According to the criterion adopted, this approach has two variants, allowing feature selection either for optimal representation or for discrimination.