搜索资源列表
Kjunzhijulei
- 用于说话人识别初始化样本的聚类算法 调试成功-Speaker Recognition for initialization of the clustering algorithm samples
GMM-GMR-v2.0
- In statistics, a mixture model is a probabilistic model for density estimation using a mixture distribution. A mixture model can be regarded as a type of unsupervised learning or clustering. Mixture models should not be confused with models for compo
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
GMM
- 高斯k均值程序算法，k-means是一种常用的聚类算法，可以实现数据的聚类。-K-means algorithm for Gaussian process, k-means clustering algorithm is a commonly used, can achieve data clustering.
clustering
- 使用K-means，混合高斯模型（GMM），层次聚类算法实现的多类别数据的聚类。内含详细的实验报告。-Using K-means, Gaussian mixture model (GMM), hierarchical clustering algorithm to achieve multi-class data clustering. Including a detailed lab report.
gmm_matlab
- GMM聚类实现，运行gmmclassfile.m文件，可实现多个数据的聚类，输入数据用.data的文件，可在gmmclassfile.m修改数据文件路径。-GMM clustering implementation
CaiDengcode
- 浙大蔡登，何晓飞写的降维，特征选择等机器学习的源码 包括：谱回归，降维，特征选择，主题模型，矩阵分解，稀疏编码，哈希，聚类，主动学习，矩阵学习。 是一个很好的机器学习源码资料。-cCaideng s code for Machine learning,include Spectral regression : (a regression framework for efficient dimensionality reduction) Dimensionality reduct
gmm_mt
- fficient GMM clustering using Multiple Threads
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,
kmeans_GMM_algorithms
- implementing k-means and GMM algorithms for clustering data points
GMM
- 聚类算法之高斯混合模型，GMM 和 k-means 很像，不过 GMM 是学习出一些概率密度函数来（所以 GMM 除了用在 clustering 上之外，还经常被用于 density estimation ）。-Gaussian mixture model of clustering algorithm, GMM and k-means like, but GMM is learning some probability density function (so GMM except on cl
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.
gmm
- Clustering of data points using Gaussian Mixture Model and EM Algorithm
GMM
- 高斯混合聚类的python实现代码，里面有data的demo(Python implementation code of Gauss mixed clustering)
GMM
- 实现了EM算法对高斯混合模型进行聚类，并将聚类结果用图像展示出来，希望对混合模型的朋友有用。(The EM algorithm is implemented to cluster the Gauss mixture model, and the clustering results are displayed with images, hoping to be useful to friends of the mixed models.)