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- Support Vector Kernel Function 支持向量核函数
- For this reason, several important properties of kernel function are discussed on the basis of support vector machine. 为此，在研究支持向量机的基础上，给出了核函数的若干重要性质。
- This paper presented a lifting wavelet to construct a new wavelet function which could be used as an allowable kernel function for support vector machine(SVM). 摘要采用提升小波方法构造出一种满足双正交的小波函数，并将这种小波函数作为支持向量机的核函数；
- For a two order polynomial kernel function based support vector classifier,the classifying function can be written in the form of the vector's components with the similar terms combined. 二阶多项式核函数支持向量机分类决策函数可以表示为待分类向量各分量的形式,其中的同类项可以合并,同类项的系数在得到支持向量后可以计算得出。
- Scaling Kernel Function Support Vector Machines 尺度核函数支撑矢量机
- RVM exploits Bayesian learning framework, which has dramatically fewer kernel functions than comparative support vector machine.So that accurate prediction models can be acquired. RVM使用贝叶斯方法推理，推广能力好，与支持向量机相比解更为稀疏，这些保证了RVM算法具有良好的预测能力。
- This paper proposes support vectors including redundant information after analyzing geometrical structure of RBF kernel function and data dependent way for improved Support Vector Machine(SVM). 在研究RBF核函数的几何特性和分析SVM数据依赖性改进方法的基础上,提出了支持向量携带数据冗余信息的论点。
- The algorithm introduces twice training of Riemannian geometry’s modifying the kernel function as well as a forgetting factor to decrease the the number of support vectors. 考虑到简化算法模型和降低计算复杂度，该算法引入遗忘因子和使用黎曼几何修改核函数的二次训练方法减少了算法的支持向量数目。
- admissible support vector kernel 容许支持向量核
- In this class we discuss some results and open problems related to the construction and choice of the appropriate kernel functions for Support Vector Machines and Regularization Networks. 这堂课我们将讨论且提出有关支持向量机和调控网络建构与选择适当的核心函式运作的一些结果和问题。
- Support vector machine and kernel function characteristic analysis in pattern recognition 支持向量机在模式识别中的核函数特性分析
- An Improved Method for Kernel Function with Data-Dependent Type of Support Vector Machine 支持向量机的数据依赖型核函数改进算法
- Influence to Nonlinear Classification Support Vector Machines by Separable Variables Kernel Function 变元可分离核函数对非线性支持向量分类机的影响
- Identifying the Parameters of the Kernel Function in Support Vector Machines Based on the Grid-Search Method 基于网格搜索的支持向量机核函数参数的确定
- A Study of Personal Credit Scoring Models on Support Vector Machine with Optimal Choice of Kernel Function Parameters 基于支持向量机的个人信用评估模型及最优参数选择研究
- Fusion of Domain Knowledge and Model Based on Support Vector Permutation Kernel Function 基于支撑向量置换核函数的一种领域知识与模型融合的技术
- face recognition; support vector machines; optimal separate hyperplane; kernel function; primary component analysis; wavelet transform. 01人脸识别;支持向量机;最优分类面;核函数;主分量分析;小波变换
- Be aimed at the automatic choosing function of support vector machine on feature selection,we submit an improved minimal kernel classifiers. 针对支持向量机在特征选择方面具有自动选择的功能,提出了一种改进的最少核分类器。
- Theoretically how to choose Kernel function remains unsolved. 在理论上，怎样选择核函数，还是一个未解决的问题。
- Keywords amino acid descriptor;peptide;QSAR;kernel function;support vectors regression; 肽;定量构效关系;核函数;支持向量回归;性能评价;
