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stprtool.rar
- 统计模式识别工具箱（Statistical Pattern Recognition Toolbox）包含： 1，Analysis of linear discriminant function 2，Feature extraction: Linear Discriminant Analysis 3，Probability distribution estimation and clustering 4，Support Vector and other Kernel Machines,
Kernel_Methods_for_Pattern_Ana
- 该文档包含了描述核方法的经典书籍Kernel+Methods+for+Pattern+Analysis以及附带书中的源码，非常适合学习核方法的研究者，希望大家喜欢～,this document include the classic book Kernel+Methods+for+Pattern+Analysis which describs the kernel trick in detail, and with the souce code in it, hope you will like
kernel_pca
- Kernel principal component analysis (kernel PCA) [1] is an extension of principal component analysis (PCA) using techniques of kernel methods. Using a kernel, the originally linear operations of PCA are done in a reproducing kernel Hilbert space with
sph1
- The smooth particle hydrodynamics (SPH), the diffuse element method (DEM), the element-free Galerkin method (EFGM), the reproducing kernel particle method (RKPM), the moving-particle semi-implicit method (MPS) are among others. However, it seem
SVM-KM
- 基于MATLAB平台的 KM-SVM算法源码-Kernel Methods for Pattern Analysism based on matlab
KERNEL-PCA
- Kernel principal component analysis (kernel PCA) is an extension of principal component analysis (PCA) using techniques of kernel methods. Using a kernel, the originally linear operations of PCA are done in a reproducing kernel Hilbert space with a n
Kernel
- Kernel methods for feature extraction
sparsekernelmethods_Code
- 稀疏核方法的逼近算法,Matlab实现，非常快速。-sparse kernel methods
BP-network-test-report
- BP网络表达傅里叶核函数,此次实验采用了两种方法，第一方法是在matlab中实现BP算法，然后用实现的BP算法实现对傅里叶核函数的逼近，第二种方法是调用matlab中的工具箱函数实现傅里叶和函数的逼近。-BP Network expression Fourier kernel, the experiments using two methods, the first method is to achieve BP algorithm in matlab, then use the BP algo
mutli-output
- 多输出的支持向量机matlab代码, 常规的svm是单输出，这个是多输出- Standard SVR formulation only considers the single-output problem. In the case of several output variables, other methods (neural networks, kernel ridge regression) must be deployed, but the good properties of
KernelDictionary
- 基于核函数的字典学习方法，包含KSVD，OMP以及核KSVD和核OMP方法。可用于字典学习或稀疏表示。-Dictionary-based learning kernel, including KSVD, OMP and OMP nuclear KSVD and nuclear methods. It can be used for learning dictionary or a sparse representation.