搜索资源列表
Em
- 使用k均值算法计算聚类的重心，并用EM算法计算各聚类的参数-Using k-means clustering algorithm to calculate the center of gravity, and using EM algorithm to calculate the parameters of each cluster
kmean
- k-means algorithm算法是一个聚类算法的实现及详细说明-k-means algorithm
clustering-problem-
- 关于matlab解决聚类问题的相关程序，包含蚁群算法和K均值算法，可以一看，部分附带程序，非本人原创。-About matlab to solve clustering problem related procedures, including the ant colony algorithm and K-means algorithm, one can see, some incidental proceedings, not my original.
SNFAP
- 这是基于吸引子传播算法的改进，采用svd技术，还有半监督思想，有效提高聚类效果-K-nearest neighbor algorithm based on neural networks, and k-means for effective integration and improvement, improved k-means algorithm
clarify-PSO
- 协同PSO算法是运用协同组合方法，采用K均值来分类，PSO辅助来实现聚类分析-PSO algorithm is the use of collaborative synergistic combination of methods, the use of K-means to classify, PSO assisted to achieve clustering analysis
fuzzy-control
- 模糊控制的程序。一，对样本进行聚类分析，以此来确定模糊规则个数。二，利用K-means法对样本聚类。三，参数修正过程。-The example of fuzzy control
classify_su
- K-均值算法与聚类算法以及实现了简单的识别功能-K-means clustering algorithm and the realization of a simple recognition
cluster-toolbox
- 聚类工具箱,可以实现k-means，fuzzy c-means，agglomerative (hierarchical) clustering等聚类-cluster toolbox
clustering-on-matlab-kmeans
- 很好的应用在聚类上的关于K-MEANS算法，应用平台是MATLAB，算法简单明了，目的清晰，结果很好。-Good application in clustering on K-MEANS algorithm, application platform is MATLAB, the algorithm is simple and clear, the purpose of clarity, the result is very good.
kmeans
- k-means 算法用java实现对二维点集合的分类 输入相应的类别数 选择聚类中心-k-means algorithm to classify the input using java-dimensional set of points corresponding to the number of categories to select the cluster centers
Untitled1
- 聚类算法举例，初学K-均值算法，应用实例说明算法如何实现。-Clustering algorithm, for example, novice K-means algorithm, application examples illustrate how to implement the algorithm.
stprtool_v2.12
- 统计模式识别工具箱(STPRTool 版本2.12 2013-09-12) 功能有线性判别函数、特征提取、密度估计和聚类、支持向量机、贝叶斯分类器、交叉验证等-Statistical Pattern Recognition Toolbox Methods: Fisher,PCA,GMM,K-means,SVM,Bayes classifier,Cross-validation,KNN,etc.
all-of-Cluster
- 大多数经典聚类分析算法的matlab实现，包括K均值、模糊聚类（FCM）、SOM、Kohonen、EM、DBSCAN、等！-ON划词翻译ON实时翻译 Most of the classical clustering algorithm matlab implementation, including K means, fuzzy clustering (FCM), SOM, Kohonen, EM, DBSCAN, etc.!
canopy
- 一种新的聚类方法，结合k-means，用Python作为开发工具-a kind of clustering
cluster_SVM
- Clustering 和 SVM 结合的预测模型算法。聚类采用k-means方法，SVM采用lib-svm工具箱。-kMeans and SVM(support vector machine) prediction model is provided.
cluster
- python语言实现k-means算法和Fast Search And Find Of Density Peaks算法用于文本聚类，-python language implements k-means algorithm and Fast Search And Find Of Density Peaks for text clustering algorithm,
KMeans
- K-means算法的实现,通过对没有标记的原始数据进行kmeans聚类得到的分类。-K-means algorithm to achieve
kmeansInJava
- 使用Java实现了kmeans算法，对给定点阵进行聚类-implementing k-means algorithm using java to clustering the given points
kmeas
- k-means，经典聚类算法DBSCAN的MATLAB实现，简单易懂，可以运行-k-means，Classical clustering algorithm concentration of MATLAB implementation, easy to understand, you can run
DataMiningCluster-master
- 数据挖掘的聚类算法实现 Implementation of text clustering algorithms including K-means, MBSAS, DBSCAN-data mining cluster