针对支持向量机(Support Vector Mechine)学习泛化才能强白勺特点,并考虑其寻优才能较弱白勺不足,将粒子群算法(Particle Swarm Optimization Algorithm)引入到最小二乘支持...
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本文针对支持向量机参数选取问题，研究基于支持向量机参数优化的木材干燥过程建模。
This paper researched on the modeling of wood drying process based on parameters optimization of SVM to aim at the problem of its parameters selection.
第三，针对支持向量机算法复杂度较高，难以应用于大样本分类的问题，提出了GMP-CSVC算法。
Thirdly, a GPU based massively data parallel C-SVM classification (GMP-CSVC) algorithm is presented to reduce the training time of SVM.
针对支持向量机学习是一种有导师的学习，引入了否定算法，把人脸特征否定的结果来供支持向量机学习。
Because the learning support vector machine is an instructing learning, a negative algorithm is introduced. The negative result of facial feature is provided for the support vector machine learning.
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