Taking advantage of class-specific feature selection
IDEAL'09 Proceedings of the 10th international conference on Intelligent data engineering and automated learning
A multi-resolution hidden Markov model using class-specific features
IEEE Transactions on Signal Processing
General framework for class-specific feature selection
Expert Systems with Applications: An International Journal
Journal of Visual Communication and Image Representation
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In this correspondence, we present a new approach to the design of probabilistic classifiers that circumvents the dimensionality problem. Rather than working with a common high-dimensional feature set, the classifier is written in terms of likelihood ratios with respect to a common class using sufficient statistics chosen specifically for each class