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The least squares support vector machine (LS-SVM) has emerged as a popular data-driven modeling method and been extensively studied in the machine learning community. However, the LS-SVM is sensitive to noisy data and may not be effective when the level of noise is high. In this paper, a probabilistic LS-SVM is proposed to have a more reliable performance. First, a distributed LS-SVM is constructed...
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