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Software fault prediction (SFP) is useful for helping the software engineer to locate potential faulty modules in software testing more easily, so that it can save a lot of time and budgets to improve the software quality. In this paper, aiming at solving the problem that the faulty samples are too rare to train a classifier, an one-class SFP model is proposed by using only non-faulty samples based...
This paper focuses on developing classification algorithms for problems in which there is a need to predict the class based on multiple observations (examples) of the same phenomenon (class). These problems give rise to a new classification problem, referred to as set classification, that requires the prediction of a set of instances given the prior knowledge that all the instances of the set belong...
Aim at the robustness of predictive control and on-line modeling, an on-line predictive control based on least squares support vector machine (LS-SVM) is proposed. In order to carry out on-line learning, the training data threshold is set through discussing the theory of LS-SVM and the character of control system. Then the model of the on-line predictive control system is established, and the analytical...
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