We address the problem of efficiently learning Naive Bayes classifiers under classconditional classification noise (CCCN). Naive Bayes classifiers rely on the hypothesis that the ...
Artificial Immune Systems (AIS) constitute an emerging and promising field, and have been applied to pattern recognition and classification tasks to a limited extent so far. This ...
Aris Lanaridis, Vasileios Karakasis, Andreas Stafy...
This paper proposes an efficient three-stage classifier for handwritten digit recognition based on NN (Neural Network) and SVM (Support Vector Machine) classifiers. The classifica...
Abstract. We present a survey of recent results concerning the theoretical and empirical performance of algorithms for learning regularized least-squares classifiers. The behavior ...
We investigate how stack filter function classes like weighted order statistics can be applied to classification problems. This leads to a new design criteria for linear classifie...
Reid B. Porter, Damian Eads, Don R. Hush, James Th...