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heguji
- 非参数统计学中非参数回归的简单应用核回归程序，应用范围广泛，不需要知道样本的分布就可以使用该方法。-Non-parametric statistical regression Nonparametric kernel regression of the simple application procedure, a wide range of applications, does not need to know the distribution of the samples you can u
KDE
- Bivariate Kamma Kernel Density Estimate for large data set-optimize method
coLinux-0.7.4
- Cooperative Linux, 簡稱 coLinux, 是一種對 Linux kernel 的移植, 讓一台機器可以協同運作不同的作業系統. coLinux 的前身 UMLWin32 最早是由 Dan Aloni 在 2000 年所開發, 當時的目的是為了將 User Mode Linux 移植到 Cygwin 上. 在 2003 年時, Dan Aloni 運用了不同以往的想法與做法, 於是, 便產生了 coLinux. coLinux 不同於 VMware 等模擬器, coLinu
KKPCA
- 用核主成成分分析法对数据的降维，根据降维结果可选择最合适的维数-Kernel principal component analysis with the data dimension reduction method, based on the results of dimension reduction can choose the most appropriate dimensions
KPCA
- 核主成分分析是一种流行的非线性特征提取方法- Kernel principal component analysis is a popular nonlinear feature extraction method
kpca
- 核主成分分析方法是主成分分析的改进算法，其采用非线性方法提取主成分-Kernel principal component analysis method is an improved algorithm of principal component analysis, which uses a nonlinear principal components extracted
mulimodel-data-and-feature-selection
- 多模态数据的特征提取方法：时间序列数据及DTW高斯核,图像数据及直方交核 和字符串数据及字符串核-Feature extraction method of multi modal data, time series data and DTW Gauss, the image data and the histogram intersection kernel and string data and String Kernel
G_pravin_zhq
- 基于核函数展开法的hankel变换的算法（主要是pravin的方法和zhq的方法）-Algorithm based on kernel function expansion method hankel transform (mainly pravin zhq methods and methods)
simple-mkl-python-master
- 多特征融合的分类方法,主要实现多核函数的分类归纳从而比较单核函数下特征描述不足(The classification method of multiple feature fusion mainly realizes the classification and induction of multi kernel functions, thus comparing the feature descr iption of single kernel function)
盲源分离
- 常用的盲分离算法有二阶统计量方法、高阶累积量方法、信息最大化（ Infomax ）以及独 立成分分析（ ICA ）等。这些方法取得最佳性能的条件总是与源信号的概率密度函数假设有关， 一旦假设的概率密度与实际信号的密度函数相差甚远，分离性能将大大降低。本文提出采用 核函数密度估计的方法进行任意信号源的盲分离，并通过典型算例与几种盲分离算法进行了 性能比较，验证了方法的可行性。(The commonly used blind separation algorithms include
css3lightbox
- Suitable for use in PHP to build online galleries, albums, for photo browsing and display. Drag the picture to move anywhere. Click zoom to get one and the next to play! Using the directory direct reading method, without too many settings, you can re
程序
- 以稀疏子空间聚类以及低秩子空间聚类等基本谱聚类算法为基础，通过 运用核映射算法，融合与数据本身结构相关的局部切线空间函数以及主成分分析 算法建立了可以应对独立子空间聚类、非独立子空间聚类、非线性聚类、混合多 流体聚类问题以及多种含有大数据量的实际问题，包括处理运动分割、人脸识别、 工件识别等情况中的多种类型数据分类的聚类算法，并且引入 Map-Reduce 并行处 理方法优化了算法的计算效率(Based on the basic spectral clustering algorith
kPCA_v3.1 (1)
- KPCA用于数据特征的降维，先通过核方法，将样本映射到高维空间，再进行主成分分析过程。(KPCA is used to reduce the dimension of data, first through the kernel method, the sample is mapped to high-dimensional space, and then the principal component analysis process.)
Package'kernlab'使用说明文档2012版
- R语言中的kernlab包使用说明手册，kernlab是R语言中一个常用的机器学习包，为基于核函数的学习方法提供了一个灵活的框架(The kernlab package instruction manual in R language. Kernlab is a commonly used machine learning package in R language. It provides a flexible framework for kernel based learning metho
kernel_eca-master
- Kernel Entropy Component Analysis,KECA方法的作者R. Jenssen自己写的MATLAB代码，文章发表在2010年5月的IEEE TPAMI上面-Kernel Entropy Component Analysis, by R. Jenssen, published in IEEE TPAMI 2010.(We introduce kernel entropy component analysis (kernel ECA) as a new method fo
KFCM-master
- 基于核方法的模糊C均值聚类，考虑到空间数据之间的相关性，结合各点的邻域信息，在原代码中添加邻域信息：(The fuzzy C mean clustering based on kernel method, considering the correlation of spatial data and combining the neighborhood information of each point, adding neighborhood information to the origin
led_drv_platform_platdata
- 1，实现入口函数 xxx_init()和卸载函数 xxx_exit() 硬件部分初始化构建 file_operation结构 (与内核相关) 实现操作硬件方法 xxx_open,xxx_read,xxxx_write...(与硬件相关)(1, implement the initialization of the entrance function xxx_init () and the uninstall function xxx_exit () hardware part to initi
KECA_Journal_Article
- Robert Jenssen 撰写论文原文(We introduce kernel entropy component analysis (kernel ECA) as a new method for data transformation and dimensionality reduction. Kernel ECA reveals structure relating to the Renyi entropy of the input space data set, estimated