Simultaneous Design of Feature Extractor and Pattern Classifier Using the Minimum Classification Error Training Algorithm

~ Recently, a minimum classification error training algorithm has been proposed for minimizing the misclassification probability based on a given set of training samples using a generalized probabilistic descent method. This algorithm is a type of discriminative learning algorithm. but it approaches the objective of nlininlumclassification error in a more direct manner than the conventional discriminative training algorithms. We applv this algorithm for simultaneous design of featlure ext,ractor and pattern classifier. and demonstrate some of its properties and advantages.