搜索资源列表
FCM[matlab]
- FCM,模糊C均值聚类的MATLAB实现[matlab]-FCM, Fuzzy C- Means clustering MATLAB [Matlab]
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)
rbf_Kmeans
- 一个基于K均值聚类的ＲＢＦ神经网络，注释写的很明白，有不明白的地方可以发邮件问我。-a K-means clustering based on the RBF neural network, notes written very well, did not understand the local mail can ask me.
Cluster111
- C-均值动态聚类算法 matlab 很简单对 一组样本点的分类和中心点-C- Means clustering algorithm Matlab is very simple sample of a point and focal point for the classification
yk-kMEANS_3
- k-均值算法实现聚类，已经带有测试数据，vc++6-k-means clustering algorithm has been tested with data vc 6
DataMining20070102
- DataMining软件(集成了关联规则、k-均值聚类、模糊聚类、k-中心点聚类四种算法) -DataMining software (integrated association rules, k-means clustering, fuzzy clustering, k-center clustering of four algorithms)
KAVERAGE
- 图像检索中的K—均值聚类，以及改进的K——均值聚类算法
KMEANSII
- 神经网络中的K均值聚类算法II： 1.KMIn为输入数据文本，其中，第一个参数为所要聚类点个数，第二个参数为聚类点的维数,第三个参数为所要求聚类的个数 2.KM2OUT为经过K均值聚类算法II计算后得到的结果-Neural network in K-means clustering algorithm II: 1.KMIn input data for the text, of which the first parame
c-jun
- 模式识别的聚类方法：C－均值算法，求得不同的分类-Pattern Recognition Clustering Method: C-means algorithm to obtain the classification of different
Kmeans
- 包含两个文件KMEAN.h,KMEAN.CPP,使用方法非常简单，将数据存成.dat文件，即可对其进行Ｋ均值聚类-Consists of two documents KMEAN.h, KMEAN.CPP, very simple to use, the data saved as. Dat file can be K-means clustering
Kmean_c
- 聚类分析最基本的K均值算法的C语言实现程序-Cluster analysis of the basic K-means algorithm of C language procedures realize
k-means
- 数据挖掘中的k均值算法，应该属于聚类分析的，c语言版。-Data Mining k-means algorithm, should belong to cluster analysis, c language version.
KMEAN
- 聚类分析算法中的最基本的K均值算法C++实现程序-Cluster analysis algorithm of the basic K-means algorithm C++ Realize procedures
NetCreate
- 现有的几个网络拓扑随机发生器，其实很难生成理想的网络拓扑结构，其主要原因在于很难控制节点的疏密和间距。我们提出来的这个改进算法，在随机抛撒节点的时候使用了K均值聚类，由本算法作为网络拓扑发生器，网络节点分布均匀且疏密得当，边的分布也比较均衡-The few existing random network topology generator, is in fact very difficult to generate the desi
K-SA
- 此文档是K类均值聚类和模拟退火结合的软硬件化分算法。众所周知，模拟退火算法的通用性，此算法是模拟退火的改进，较单纯的SA更优秀。-This document is a category K-means clustering and simulated annealing combination of hardware and software sub-algorithm. As we all know, the generic simu
FCM
- 利用java编写的模糊C均值聚类算法，可以用来图像无监督聚类及图像分割等。-Using java prepared Fuzzy C-means clustering algorithm, can be used to image non-supervised clustering and image segmentation and so on.
AimprovedFuzzyCMeans
- 关于模糊c-均值算法改进及其对卫星遥感数据聚类的对比，文章对模糊c-均值算法提出一改进意见，并通过实践证明。-On the fuzzy c-means algorithm to improve its impact on satellite remote sensing data clustering contrast, article on the fuzzy c-means algorithm to improve the one
kmedia
- 用matlab语言实现k均值的模式识别的聚类算法-Matlab language used k-means clustering algorithm for pattern recognition
cluster_algorithm
- 包括分解聚类算法和k-均值聚类算法，内有用到的数据文本文件，开发环境Visual Studio .NET2003-Including the decomposition clustering algorithm and k-means clustering algorithm, with useful data to a text file, development environment Visual Studio. NET2003
FCM_Cluster
- FCM算法是一种基于划分的聚类算法，它的思想就是使得被划分到同一簇的对象之间相似度最大，而不同簇之间的相似度最小。模糊C均值算法是普通C均值算法的改进，普通C均值算法对于数据的划分是硬性的，而FCM则是一种柔性的模糊划分。-FCM algorithm is a clustering algorithm based on the division of its thinking is that it is making is divide