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
- 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
- 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.)