For two-class classification, it is common to classify by setting a threshold on class probability estimates, where the threshold is determined by ROC curve analysis. An analog fo...
An estimation of the generalization performance of classifier is one of most important problems in pattern clasification and neural network training theory. In this paper we estima...
In a previous paper [1], we have presented a new linear classification algorithm, Principal Component Null Space Analysis (PCNSA) which is designed for problems like object recogn...
This paper proposes and evaluates error detection and recovery mechanisms suitable for embedded systems. The purpose of these mechanisms is to provide detection of and recovery fr...
A new procedure for learning cost-sensitive SVM classifiers is proposed. The SVM hinge loss is extended to the cost sensitive setting, and the cost-sensitive SVM is derived as the...