Ps22Pdf 关键词 : 统计学习理论 ; 支持向量机 ; 训练算法 [gap=639]Key words: Statistical Learning Theory; Support Vector Machine; Training Algorithms
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intrusion training algorithms 入侵训练算法
fast training algorithms 快速训练算法
batch training algorithms 批训练算法
hybrid training algorithms 混合学习算法
There are few studies on online SVM training algorithms. Based on previous research results, incremental SVM training algorithm is deeply studied in this thesis.
然而这些算法无一例外都是只能够离线应用的训练算法,对支持向量机在线训练算法的研究还很少,因此本文在已有成果的基础之上,重点地研究了增量型的支持向量机训练算法。
参考来源 - 增量型支持向量机回归训练算法及在控制中的应用·2,447,543篇论文数据，部分数据来源于NoteExpress
The neural networks structure design, learning samples and training algorithms are expounded.
阐明了神经网络状态选择器的结构设计、样本选取及训练方法。
A novel PNN model with training algorithms is proposed for class conditional density estimation.
提出了一种新的类条件密度函数估计的PNN模型及其算法。
Under large samples, it is considerable complex to solve SVM questions by traditional methods. A series of training algorithms are discussed and compared.
在大训练样本情况下，用传统的方法求解SVM问题计算复杂，针对该问题探讨了一系列的SVM训练算法，并对其进行了比较。
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