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The performance and regression precision of weak learners (accuracies should be greater than 0.5) for pattern recognition and forecasting can be upgraded using AdaBoost algorithm. Support vector machine (SVM) is a state-of-the-art learning machines and have been widely used in pattern recognition area since 90's of 20th contrary, however the performance of SVM is not stable and easily influenced due...
A new incremental learning method for support vector machine (SVM) is proposed, which train SVM quickly and incrementally. In this paper, we first choose the violating KKT samples which maybe be new support vector candidates. Then for a given new-added sample, the proposed training method validate whether they are border vectors. If true, we add them to training sample set to retrain support vector...
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