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k均值聚类算法分析
- k均值聚类算法分析，采用C++编程技术，提供代码可重用机制 -k-means clustering algorithm analysis, the use of C programming, code reuse mechanism
K-Mean1
- 编写K-均值聚类算法程序，对下图所示数据进行聚类分析(选k=2)-prepare K-means clustering algorithm, the data shown in the chart below cluster analysis (EAC k = 2)
kcluster
- 一种基于软划分方法的聚类方法——模糊k均值法聚类分析。-A division of methods based on soft clustering method- fuzzy k-means cluster analysis.
K-means
- K-均值聚类分析，程序不完整,急需下载东西，所以出此下策，请谅解！-K－means Clustering
KMEANS
- 利用数据挖掘知识和c实现K-均值聚类分析-The use of data mining knowledge and c to achieve K-means clustering analysis
zfk_example
- 聚类分析里的k均值（kmeans）算法的matlab实现，是老师即将出的书里，我给写的例子，大家看看吧。 -Where k-means cluster analysis (kmeans) algorithm matlab implementation, a teacher is leaving the book, I give examples of writing, we take a look at bar.
Kmeanjulei
- k均值聚类分析，比较简单，只适合学习使用个，不适合数据处理。-k-means clustering analysis, relatively simple, only suitable for learning to use one, not suitable for data processing.
kmeans
- 使用K－均值聚类算法在IRIS数据上进行聚类分析.-K-means clustering algorithm using IRIS data in the cluster analysis.
k
- 模式识别中的K均值聚类分析方法，该方法力偶那个迭代过程来进行处理，一步步逼近结果-Pattern Recognition Analysis of K-means clustering method Couple iterative process to deal with that, step by step approach results
ClusteringStatic
- 聚类分析算法,k均值聚类分析算法c++源码-clustering statics
k_means_cluster
- k均值聚类算法 ，c语言实现 了基于均值的聚类分析，同时增加了多维向量分析功能，使得聚类的收敛速度更快。-k means clustering algorithm, c language implemented based on the mean cluster analysis, while increasing the multi-dimensional vector analysis functions, making the convergence faster clustering.
k-means-clustering-of-rbf-
- 聚类算法：聚类分析是指事先不了解一批样品中的每一个样品的类别 基于k均值聚类学习算法的rbf神经网络实现-Clustering algorithm: cluster analysis is the prior knowledge of each batch of samples in the sample of category learning algorithm based on k means clustering of rbf neural network
k
- 用K均值聚类分析把多组数据分成两类 本程序为给定20组数据（用矩阵A表示）分成B、C两组。-K-means clustering analysis of the multiple sets of data into two categories This program is given 20 sets of data (represented by the matrix A) into B, C groups.
聚类分析程序
- 聚类分析程序 包括系统聚类 样品系统聚类 变量系统聚类 K均值聚类 模糊C均值聚类(Cluster analysis program)
fenlei
- K均值聚类分析，可实现2/3/4类的分类，适用于初学者，为实现5/6类的分类提供想法(k-means clustering analysis)
k-means算法2
- 使用该算法可以实现数据的聚类分析，非常适合初学者。(The algorithm can be used to achieve clustering analysis of data, ideal for beginners.)
基于聚类的细分研究
- 使用R语言进行聚类分析的例子，包括层次聚类，k均值聚类，密度聚类等(Examples of clustering analysis using R language, including hierarchical clustering, K mean clustering, density clustering, etc.)
聚类分析程序
- 包含了各类聚类分析程序。主要包括系统聚类，基于欧氏距离的聚类，变量系统聚类和K均值聚类(It includes all kinds of cluster analysis programs. It mainly includes system clustering, Euclidean distance based clustering, variable system clustering and K-means clustering)
Matlab聚类分析
- 分别运用分层聚类、K均值聚类以及高斯混合模型来进行分析
k均值聚类
- 通过比较自编MATLAB 的k-means 算法程序和SPSS 中自带的k-means聚类工具，对两个数据集聚类，并分析了聚类结果。(By comparing the k-means algorithm program of self-compiled MATLAB with the K-means clustering tool of SPSS, two data sets are clustered and the clustering results are analyzed.)