搜索资源列表
emgmm
- EM算法估计GMM的matlab版本的源代码，适合给类机器学习问题-EM algorithm estimates GMM Matlab version of the source code, suitable for the type of machine learning problems
GMM-GMR-v1.2
- 这是一款用matlab编写的GMM算法，有样例，实现用EM算法寻找GMM参数-This is a matlab prepared using GMM algorithm, there is a sample, look for implementation using EM algorithm for GMM parameter
gmm
- 求高斯混合模型的EM算法，matlab程序。-Seeking EM algorithm for Gaussian mixture model, matlab program.
EM-GMM
- Em algo for GMM, data mining unsupervised learning-Em algo for GMM, data mining unsupervised learning
em-algorithm-for-gmm
- 基于高斯混合模型(GMM)的em算法，给出了其matlab实现-em algorithm for GMM
emgm
- em for n-dimensional g-em for n-dimensional gmm
em
- EM算法的Matlab实现，针对GMM模型-EM algorithm for GMM Model
GM_EM
- 不错的GM_EM代码。用于聚类分析等方面。- GM_EM- fit a Gaussian mixture model to N points located in n-dimensional space. Note: This function requires the Statistical Toolbox and, if you wish to plot (for k = 2), the function error_ellipse Elem
GMM
- 程序展示了使用EM algorithm来训练GMM(Gaussian Mixture Model)来进行binary classification。-Program demonstrates the use of EM algorithm to train the GMM (Gaussian Mixture Model) for binary classification.
GM_EM
- 经典的em算法即期望最大化算法，可用于高斯混合GMM模型和聚类算法，-Classic em algorithm that expectation maximization algorithm can be used for Gaussian mixture models and GMM clustering algorithm,
mixBern
- Just like EM of Gaussian Mixture Model, this is the EM algorithm for fitting Bernoulli Mixture Model. GMM is useful for clustering real value data. However, for binary data (such as bag of word feature) Bernoulli Mixture is more suitable.
em
- em算法介绍:EM算法有很多的应用，最广泛的就是GMM混合高斯模型、聚类、HMM等等(This is the EM algorithm using JAVA, easy to understand, easy to use and helpful for understanding the EM algorithm)
GMM_EM
- GMM算法是混合高斯模型，其求解过程需要不断迭代，本程序利用EM算法进行了仿真实现，可以加深对GMM的理解。(GMM algorithm is a hybrid Gauss model, and its solution process needs iteration. This program uses EM algorithm for simulation, which can deepen the understanding of GMM.)
EM-GMM.py
- Gaussian mixture 的 EM算法(EM algorithm for Gaussian mixture model)