搜索资源列表
kernel-kmeans
- 实现kernel k-means 聚类，可以处理非线性数据-Implement kernel k-means clustering, can handle nonlinear data
LSSVM
- 最小二乘支持向量机，程序粘到command window里，设定 2 两个参数，可以更改，以达到最优化-igam=0.001 isig2=0.001 [gam,sig2]=tunelssvm({X,Y, f ,igam,isig2, RBF_kernel },... [0.001 0.001 10000 10000], gridsearch ,{}, leaveoneout_lssvm ) type= function approximation kernel= RBF_
steven2358-kmbox-v0.11-0-g425fe66
- 核方法工具箱，包括核典型相关分析KCCA，KPLS等算法的源码和实现。-Kernel Methods Toolbox KMBOX includes implementations of algorithms such as kernel principal component analysis (KPCA), kernel canonical correlation analysis (KCCA) and kernel recursive least-squares (KRLS).
gplvm
- 这是一个用于高斯过程隐变量模型的工具箱，其中包含了MATLAB/C/PYTHON三种语言版本-As of July 2005 a C++ implementation of the GPLVM exists which has most of the flexibility of this software but runs much faster. However as of this time it cannot handle very large data sets as the spar
NaiveBayesClassifier.m
- I use Matlab 2008a which does not support Naive Bayes Classifier. scr ipt supports normal and kernel distributions. Statistics toolbox for 2008a version is used in the scr ipt. Also includes function for confusionmat
kde2d
- 二维高斯核函数重构 重构方法不依赖于参数化模型-2D Gaussian Kernel Reconstruction fast and accurate state-of-the-art bivariate kernel density estimator with diagonal bandwidth matrix. The kernel is assumed to be Gaussian. The two bandwidth parameter
kernelpca_tutorial
- 基于R语言的kernel矩阵生成代码，已包含高斯核，可以修改核函数-R language based on the kernel matrix generation code, has included the Gauss kernel, you can modify the kernel function
svr-kernel-function-version
- 用matlab实现了支持向量回归，并且使用了核函数，对于各种维度的数据均可使用-Using matlab to achieve an SVR, and uses kernel functions for the various dimensions of the data can be used
K-LDA
- KFDA是FDA进行首先投影到核空间，然后进行判别分析，核技巧提高了算法的可行性。-KFDA said the FDA is first projection in kernel space, and then the discriminant analysis, nuclear techniques to improve the feasibility of the algorithm.
waveletkernel
- 这是一个小波核函数工具包，可根据需要的核函数公式构建自己所需的核，可用于核学习方法。-The wavelet kernel function is a toolkit, can according to need to build your kernel function formula for nuclear, and can be used to study method.
java网络爬虫
- 是一个无须配置、便于二次开发的JAVA爬虫框架（内核），它提供精简的的API，只需少量代码即可实现一个功能强大的爬虫(Is a JAVA reptile framework (kernel) that does not need to be configured for easy development. It provides a streamlined API that requires a small amount of code to implement a powerful crawl
FNN与PCA和KPCA结合
- 一种特征提取方法：结合主元分析(PCA)和核主元分析（KPCA）的前馈神经网络（FNN）(A feature extraction method: the feedforward neural network (FNN) combined with principal component analysis (PCA) and kernel principal component analysis (KPCA))
核主元分析（Kernel principal component analysis ，KPCA）在降维、特征提取以及故障检测中的应用
- 主要功能有： （1）训练数据和测试数据的非线性主元提取（降维、特征提取） （2）SPE和T2统计量及其控制限的计算 （3）故障检测 KPCA的建模过程（故障检测）： （1）获取训练数据（工业过程数据需要进行标准化处理） （2）计算核矩阵 （3）核矩阵中心化 （4）特征值分解 （5）特征向量的标准化处理 （6）主元个数的选取 （7）计算非线性主成分（即降维结果或者特征提取结果） （8）SPE和T2统计量的控制限计算