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Active Set Fuzzy Support Vector Epsilon-Insensitive Regression Approach

机译:主动集模糊支持向量Epsilon不敏感回归方法

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In this paper a new fuzzy linear support vector machine formulation for regression problems is proposed and solved by the active set computational strategy. In this model, to each input data a fuzzy membership value is associated so that the input data can contribute proportionally to the learning of the decision surface. The proposed method has the advantage that its solution is obtained by solving a system of linear equations at a finite number of times rather than solving a quadratic optimization problem. Numerical experiments have been performed and the results obtained are in close agreement with the exact solution of the problems considered which clearly shows the effectiveness of the method.
机译:本文提出了一种新的用于回归问题的模糊线性支持向量机公式,并通过主动集计算策略进行求解。在此模型中,模糊隶属度值与每个输入数据相关联,以便输入数据可以成比例地有助于决策面的学习。所提出的方法的优点在于,其解决方案是通过有限次数地求解线性方程组而不是解决二次优化问题而获得的。进行了数值实验,获得的结果与所考虑问题的精确解决方案非常吻合,清楚地表明了该方法的有效性。

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