SVM kernel function is one of the most critical factors that affect the recognition rate.
SVM核函数是众多影响识别率因素中最明显的。
The key technology improves the system recognition rate is the SVM kernel function and parameter optimization.
该系统提高识别率的技术关键是SVM核函数的选取及其参数优化。
With SVM, there is no a uniform mode to choice SVM's kernel function and its parameters.
在SVM学习中，对SVM的核函数及其参数的选择还没有形成一个统一的模式。
The selection of the kernel function parameter and error penalty factor affected the precision of the support vector machine (SVM) significantly.
核函数参数和误差惩罚因子的选择对支持向量机模型（SVM）的精度有较大影响。
In this paper, an SVM-based approach applied to predict steel quenching degree is presented, and the effects of selecting kernel function on SVM modeling are also analyzed.
本文提出了基于支持向量机模型预测钢淬透性的方法，并分析了核函数的选择对支持向量机建模的影响。
The comparison of different kernel functions for SVM shows that RBF kernel function is most suitable for recognition of grape disease.
不同分类核函数的相互比较分析表明，径向基核函数最适合于葡萄病害的分类识别。
Kernel function is the key technology of SVM, the choice of kernel will affect the learning ability and generalization ability of SVM.
核函数是SVM的关键技术，核函数的选择将影响着支持向量机的学习能力和泛化能力。
To serve this purpose, we use a grid search technique using 5-fold cross-validation to find out the optimal parameter values of various kernel function of SVM.
为了达到这个目标及保证可靠性，研究中使用网格5-折交叉确认来寻找不同核函数的最优参数。
Geological information at different depth was described by introducing a mixed window kernel function to SVM.
通过引入窗口核函数，准确地反映了不同深度的地质信息。
This paper presentes the characteristics, properties and relationship of Covering Algorithms and the kernel function of Support Vector Machines (SVM) firstly.
该文首先介绍了构造型神经网络中的覆盖算法的特点和性质，以及与支持向量机(SVM)中的核函数法的关系。
The theory of SVM is studied at first, then an ameliorated RBF kernel function is presented, based on which an improved kernel function pattern classification method of SVM is put forward.
首先分析了支持向量机原理，随后引入一种改进的径向基核函数，在此基础上，提出了一种改进核函数的SVM模式分类方法。
The nonlinear offline model of the controlled plant is built by LS-SVM with the radial basis function (RBF) kernel.
首先，用具有RBF核函数的LS-SVM离线建立被控对象的非线性模型；
The SVM (Support vector Machine) classifies the data by mapping the vector from low-dimensional space to high-dimensional space using kernel function.
而SVM(支持向量机)引进核函数隐含的映射把低维特征空间中的样本数据映射到高维特征空间来实现分类。
The comparison of different kernel functions for SVM shows that liner kernel function is most suitable for recognition of cucumber disease.
不同分类核函数的相互比较分析表明，线性核函数最适合黄瓜病害识别。
The comparison of different kernel functions for SVM shows that liner kernel function is most suitable for shape recognition of plant disease spot.
不同分类核函数的相互比较分析表明，线性核函数最适于植物病害的分类识别。
For SVM, in this paper, a kernel function selection and parameter adjustment algorithm are presented. It can get optimal parameter adjustment in a given training set.
对于SVM，本文给出了一个核函数选择与参数调整的算法，它能够对给定训练集得到最优的参数调整。
With SVM, there is no a uniform mode to choice SVM "s kernel function and its parameters."
在SVM学习中，对SVM的核函数及其参数的选择还没有形成一个统一的模式。
Two-level-classifier is designed to recognized urinary sediments. The kernel function uses the radial basis function and grid-search method is used to select the parameters of SVM.
在设计时，采用两级SVM分类器级联的方式，核函数采用径向基函数，并且用网格搜索法来选取合适的参数。
Moreover, SVM can convert a nonlinear learning problem into a linear learning problem in order to reduce the algorithm complexity by using the kernel function concept.
又由于采用了核函数思想，使它将非线性问题转化为线性问题来解决，降低了算法的复杂度。
The classification accuracy of SVM based on polynomial and radial basis function kernel were compared, and the recognition accuracy of the three categories were obtained.
通过对基于多项式核函数和径向基核函数的支持向量机分类器进行比较，并且得到三种肝脏分类的识别率。
How to choose the kernel function of the SVM classifier and function's parameters affects system's generalization and operating speed directly.
如何选择核函数的SVM分类器和函数的参数，直接影响了系统的概括和运行速度。
How to choose the kernel function of the SVM classifier and function's parameters affects system's generalization and operating speed directly.
如何选择核函数的SVM分类器和函数的参数，直接影响了系统的概括和运行速度。
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