This paper presents an adaptive and iterative support vector machine regression algorithm (CAISVR) based on chunking incremental learning and decremental learning procedures.

文中基于块增量学习和逆学习过程，提出了自适应迭代回归算法。

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In this paper, a special support vector regression machine algorithm is proposed, within which smoothing function and method to solve LC1 type functions are combined to solve Newton-type algorithm.

分别采用光滑化函数法和求解lc1函数类型方法对牛顿型算法进行研究求解。

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Based on the traditional support vector machine (SVM) for regression, a new learning algorithm of the improved SVM for regression is presented in this paper.

该文对用于回归估计的标准支持向量机(SVM)加以改进，提出了一种新的用于回归估计的支持向量机学习算法。

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