搜索资源列表
EM
- EM 算法MATLAB代码,用于数据聚类。-em algorithm which is used in data clustering.
EM-algorithm
- EM算法,是一种无监督的聚类算法,可以实现对数据的处理,对不同数据进行聚类,生成类内相似度最大-EM algorithm is an unsupervised clustering algorithm, the data processing can be achieved on different data clustering, to generate the maximum within-class similarity
GMM
- 实现混合高斯模型的聚类算法 利用最大似然估计和最大期望的方法来实现混合高斯模型-Gaussian mixture model to achieve clustering algorithm using the maximum likelihood estimation and the greatest way to achieve the desired mixed-Gaussian model
Clustering
- duke的tutorial on EM的matlab经典源码,值得一看。-Matlab code for the tutorial on Expectation Maximization,worth a visit.
gmmbayestb-v0.1.tar
- This package contains Matlab m-files for learning finite Gaussian mixtures from sample data and performing data classification with Mahalanobis distance or Bayesian classifiers. Each class in training set is learned individually with one of the three
EMGMMSeg
- GMM-EM聚类程序,输入是一维数据,很有用的程序。-GMM-EM clustering procedure, very useful.
EM_GM
- EM算法实现,是matlab主站上获得的可靠程序。-EM algorithm,which is from the matlab net about image processing.
EMAlgorithm
- 上数据挖掘课的课件,是EM算法的,其中还包括最大似然值,最大似然估计,以及cluster-data mining,EM Algorithm ,Likelihood, Mixture Models and Clustering
tf
- EM聚类算法,Knn分类算法简单C++编程-EM clustering algorithm, Knn classification algorithm is simple C++ programming
20107210374284118
- EM聚类算法的C++实现,高效地进行编码,充分利用系统资源。-EM Clustering Algorithm C++ implementation, efficient encoding, full use of system resources.
em
- 基于EM算法的模型聚类的研究及应用,GMM高斯混合模型-EM-based clustering algorithm and its application model, GMM Gaussian mixture model
EM-source
- 一个高斯混合模型,用EM算法进行聚类的例子!-A Gaussian mixture model, EM algorithm for clustering with an example!
93562307GMM-EM
- GMM-EX gmm语音转换模型,以及里面详细的ex聚类程序介绍-GMM-EX GMM voice switching model, and the EX clustering, there are detailed introduced program
clustering
- 一种基于期望最大化( E M) 算法的局部图像特征的语义提取方法。首先提取图像的局部图像特 征, 统计特征在视觉词汇本中的出现频率, 将图像表示成词袋模型; 引入文本分析中的潜在语义分析技术建立从低层图像 特征到高层图像语义之间的映射模型; 然后利用 E M 算法拟合概率模型, 得到图像局部特征的潜在语义概率分布; 最后利 用该模型提取出的图像在潜在语义上的分布来进行图像分析和理解。-Latent Semantic probability distribution using the EM
EM
- 实现EM算法的MATLAB仿真程序,利用高斯混合模型实现EM聚类算法,并比较估计参数。-EM algorithm to achieve the MATLAB simulation program, using Gaussian Mixture Model EM clustering algorithm, and compare the estimated parameters.
EM算法
- 在统计计算中,最大期望(EM)算法是在概率(probabilistic)模型中寻找参数最大似然估计或者最大后验估计的算法,其中概率模型依赖于无法观测的隐藏变量(Latent Variable)。最大期望经常用在机器学习和计算机视觉的数据聚类(Data Clustering)领域。(In statistical calculation, the expectation maximization (EM) algorithm in probability (probabilistic) maximu
高斯混合模型EM算法MATLAB程序
- 在高斯混合模型上实现聚类问题的算法。将2个高斯混合,然后尝试学习两个高斯混合后的参数。(Algorithm for clustering problem on Gauss mixture model. Mix the 2 Gauss and then try to learn the parameters after the two Gauss mixing.)
6.聚类和EM算法
- 聚类和EM算法实例,包括线性分类和非线性分类,线性回归和非线性回归(Examples of clustering and EM algorithm include linear classification and nonlinear classification, linear regression and nonlinear regression)
matlab编写的EM聚类算法
- em聚类算法,比较基础的算法,可自行改进(em clustering algorithm, more basic algorithm, self-improvement)
em
- 在统计计算中,最大期望(EM)算法是在概率模型中寻找参数最大似然估计或者最大后验估计的算法,其中概率模型依赖于无法观测的隐性变量。最大期望算法经常用在机器学习和计算机视觉的数据聚类(Data Clustering)领域。(In statistical computation, the maximum expectation (EM) algorithm is an algorithm to find the maximum likelihood estimation or the maximum