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。
Support Vector Machine for regression (SVR) has shown very good learning performance.
回归型支持向量机方法SVR具有很好的学习性能。
Support vector machine is a learning technique based on the structural risk minimization principle as well as a new regression method with good generalization ability.
支持向量机是一种基于结构风险最小化原理的学习技术，也是一种新的具有很好泛化性能的回归方法。
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