搜索资源列表
kpca_toy
- Kernel PCA的经典示例程序，非常有帮助，也很易懂。-Kernel PCA classic example of the procedure
kde.tar
- kde全称是kernel density estimation.基于核函数的概率密度估计方法。是模式识别中常用的算法之一-KDE which is kernel density estimation is used to estimate probabilty function. It is mostly used in pattern recogntion
KPCAandSVM
- KPCA与SVM共同用于人脸识别 SVM提高了分类效果 KPCA是一种借鉴SVM中核函数的一种较好的特征提取方法-KPCA and SVM for face recognition SVM together to improve the classification results from KPCA is a kernel function in SVM a better feature extraction method
kde2d
- fast and accurate state-of-the-art bivariate kernel density estimator
my_function_1
- ica 核独立主元分析（kernel independent component analysis)软件包-kica
KernelBasedObjectTracking
- A new approach toward target representation and localization, the central component in visual tracking of nonrigid objects, is proposed. The feature histogram-based target representations are regularized by spatial masking with an isotropic kernel.
kda
- kda程序 用于matlab环境下不同核函数分类问题-kda program for matlab environment classification of the different kernel function
KDE
- Bivariate Kamma Kernel Density Estimate for large data set-optimize method
Kernel_PCA
- 基于核的主分量分析方法的提出者亲自写的程序（基于MATLAB-a MATLAB m-file of Kernel PCA
KPCA_p
- 核主成分分析中使用多项式核函数时的MATLAB代码，有注释，易看懂。-Kernel Principal Component Analysis in the use of polynomial kernel function of the MATLAB code, annotated, easy read.
svm
- SVM源代码程序，包含了SVM的各个子模块-SVM source code program, including the various sub-modules of the SVM
kerneladatron
- kernel adatron, svm impelemtation using gradient ascent method, fast and accurate for solving SVM problem with two classes
kerneladatron
- Kernel adatron, solving svm with gradient ascend method. fast and accurate.
kwiener
- The following code implements a kernel Wiener Filter algorithm in MATLAB. The algorithm dependes on the eigenvalue decomposition, thus only a few thousand of data samples for training dataset is applicable so far. -The following code implement
winerfilter
- The following code implements a kernel wiener filter algorithm in MATLAB.The algorithm dependes on the eigenvalue decomposition, thus only a few thousand of data samples for training dataset is applicable so far.
KRLS
- Multivariate Online Anomaly Detection Using Kernel Recursive Least Squares
595643603713295726
- kfcm，为模糊核聚类算法，用于将低维的数据映射到高维进行分类，是较先进的算法-kfcm, the fuzzy kernel clustering algorithm for low-dimensional data is mapped to high-dimensional classification, is a more advanced algorithms
hehanshufcm
- 用Matlab实现基于核函数的C均值聚类图像分割，实验好，好用-Using Matlab implementation of kernel-based C-means clustering image segmentation, experimental is good, easy to use
pso-svm
- 这是一个用pso优化SVM中的惩罚参数C和核参数g的MATLAB源码，简单易学-This is an optimization of SVM with the pso in the penalty parameter C and kernel parameter g of the MATLAB source code, easy to learn
LWLR
- this program compare the Locally Weighted Linear Regression with three diferrent kernel function (gaussian, logistic basis, and Reciprocal Multiquadric) also compare locally weighted by simple Linear Regression.