搜索资源列表
probability-estimation
- 给定若干三维数据，建立训练概率模型，并对新数据进行估计。包括高斯模型、Parzen窗和K近邻密度估计-Given a number of three-dimensional data, the establishment of training probability model, and the new data is estimated. Including the Gaussian model, Parzen windows and K nearest neighbor density e
gmm_utilities
- This collection of MATLAB files perform operations on Gaussian mixture models (GMMs) and Gaussian kernels (ie, Parzen windows). These utilities do evaluation, sampling, multiplication, convolution, linear transformation, mixture reduction, etc. Prese
knn
- 自己写的parzen窗算法，和knn算法，在matlab2014a上运行过，无问题。-Write your own parzen window algorithm, and knn algorithm, run over on matlab2014a, no problem.
Parzen_k
- 主要内容包括两种非参数估计方法：Parzen窗估计和k最近邻估计。-The main contents include two non parametric estimation methods: Parzen window estimation and K nearest neighbor estimation.
kde
- 核密度估计,matlabkernel density estimation是在概率论中用来估计未知的密度函数，属于非参数检验方法之一，由Rosenblatt (1955)和Emanuel Parzen(1962)提出，又名Parzen窗（Parzen window）。Ruppert和Cline基于数据集密度函数聚类算法提出修订的核密度估计方法。-kernel density estimation
parzenWindowDensityEstimator
- parzen Window Density Estimator
Mulil
- Multispectral remotely sensing imagery with high spatial resolution, such as QuickBird, IKONOS satellite imagery or Aerial imagery, especially in urban scenes, often perform spectral variations and rich details within a category, resulting in
Pattern
- 模式识别的一些基本的算法，有最大最小距离分类法，简单的感知器算法，LMSE算法，以及Parzen窗函数。-Pattern recognition of some basic algorithms, have the largest minimum distance classification, simple perceptron algorithm, LMSE algorithm, as well as the Parzen window function.
knn_parzen
- a matlab code for testing k_near_neighbour and parzen window
Clustering-Hierarchical
- Clustering Hierarchical Histogram Parzen Window
parzen
- 本代码应用非参数估计法对一簇未知分布的数据进行分布函数估计- The code in the application of non parametric estimation method for estimation of the distribution function of a cluster of unknown distribution data The code in the application of non parametric
gkwj
- Parzen窗和K近邻法进行概率密度估计还带一个示波器控件()
程序
- 模式识别在MATLAB程序下的有关算法程序，包括Fisher分类，ML分类，parzen窗分类，直方图画法，roc曲线，roc分类等(Pattern recognition in the MATLAB program related algorithm program, including Fisher classification, ML classification, Parzen window classification, histogram drawing, ROC curve, RO
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
occzarence
- Parzen窗和K近邻法进行概率密度估计还带一个示波器控件()
XEWXIR
- Parzen窗和K近邻法进行概率密度估计还带一个示波器控件()
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