An incremental learning algorithm using multiple support vector machines (SVMs) is proposed.
给出了使用多支持向量机进行增量学习的算法。
In order to extend common incremental learning algorithms into a parallel computation setting, an incremental learning algorithm with multiple support vector machine classifiers is proposed.
为了将一般增量学习算法扩展到并行计算环境中，提出一种基于多支持向量机分类器的增量学习算法。
A new geometric fast incremental learning algorithm for support vector machines (SVM) was proposed.
提出了一种新的基于壳向量的增量式支持向量机快速学习算法。
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。
This algorithm, in the incremental study question, is more effective than the traditional support vector machine, with assuring the classify accuracy.
本算法在保证分类准确度的同时，在增量学习问题上比传统的支持向量机有效。
An incremental training method for support vector machine is proposed to alleviate the computing burden of large-scale, high-dimension samples in multi-component gas analyzing.
针对大规模高维气体分析样本难以计算的问题，提出一种提升的支持向量机学习方法。
To combine the attribute reduction algorithm and the incremental training algorithm of support vector machine, a support vector machine classifier based on rough set is constructed.
将属性约简算法和支持向量机增量训练算法相结合，构造基于粗糙集数据预处理的支持向量机分类器。
To combine the attribute reduction algorithm and the incremental training algorithm of support vector machine, a support vector machine classifier based on rough set is constructed.
将属性约简算法和支持向量机增量训练算法相结合，构造基于粗糙集数据预处理的支持向量机分类器。
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