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hehe3333
- 模糊c-均值算法是模糊聚类中最常见、应用最广泛的分析方法之一．经典FCM算法理论和应用的研究已经相当成熟，Bezdek业已证明算法的收敛性［6］，许多软件提供了多种方便的FCM工具箱(如Matlab中FCM工具箱等)．但是传统FCM算法处理的是普通数据集，不能直接处理区间数，得到的聚类原型也不是区间数．针对区间数，一种直觉的方法是分别对左区间值和右区间值作FCM，并把得到的聚类原型分别作为区间型聚类原型的左右区间值，但这种方法已经被证明
iriscloud
- In fuzzy cluster analysis, many algorithms have been developed. In general, the most widely used is the Fuzzy c-Means Algorithms (FCMA).-fuzzy cluster analysis, many algorithms have been developed. In genera l the most w
mohuC
- UNIX下使用的基于模糊Ｃ聚类分析的原码-use of UNIX-based C Fuzzy Cluster Analysis of the original code
fcm_c
- 模糊聚类分析传递闭包法FCM的C语言程序， 能对数据进行分类，广泛应用于模式识别中-Fuzzy cluster analysis method FCM transitive closure of the C language program that can classify the data is widely used in Pattern Recognition
Cluster
- 一个用VC编写的聚类案例，可以实现C聚类、模糊聚类和应用遗传算法对样品进行聚类分析 -Written in a cluster with VC cases, can be achieved C clustering, fuzzy clustering and genetic algorithm for cluster analysis of samples
codefcm
- fuzzy cluster means nice algorithm -fuzzy cluster means nice algorithm !!
ClusteirngAnalysis
- This work presents an implementation of a parallel Fuzzy c-means cluster analysis tool, which implements both aspects of cluster investigation: the calculation of clusters’ centers with the degrees of membership o
fuzzy_c_means
- weka聚类算法中的基础算法,可以作为实验添加到weka中，与其他算法做对比-basic alogrithm in cluster
mohuchuli
- 模糊C均值聚类算法的步骤还是比较简单的，模糊C均值聚类（FCM），即众所周知的模糊ISODATA，是用隶属度确定每个数据点属于某个聚类的程度的一种聚类算法。-Fuzzy c-means clustering algorithm steps it is quite simple, fuzzy c-means clustering (FCM), known as fuzzy membership ISODATA, it is to use
FCM
- 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 division, the idea is to make it to the same cluster is div
fcm-matlab
- matlab开发的FCM（模糊c-均值聚类算法）例程-matlab，cluster，fuzzy c-means，FCM，code
fcmfiltwa
- 用类Cluster实现一维数据的模糊C均值聚类，可在VC＋＋和BC++下使用-Class Cluster fuzzy C-means clustering, one-dimensional data can be used in VC++ and BC++
FINAL.c
- This code is clustering in wsn based on fuzzy logic and you can see network life time in this experiment and number of cluster head per round
Fcm
- FCM Data set clustering using fuzzy c-means clustering. [CENTER, U, OBJ_FCN] = FCM(DATA, N_CLUSTER) finds N_CLUSTER number of clusters in the data set DATA. DATA is size M-by-N, where M is the number of data poin
9552010E202
- This paper presents a new cluster validity index for nding a suitable number of fuzzy clusters with crisp and fuzzy data. The new index, called the ECAS-index, contains exponential compactness and separation measur
cluster-toolbox
- 聚类工具箱,可以实现k-means，fuzzy c-means，agglomerative (hierarchical) clustering等聚类-cluster toolbox
cluster-analysis
- 进行模糊C均值聚类,读取数据，并进行标准化变换-Fuzzy C-means clustering, data is read and converted to standardize
PIM-fuzzy-c-means
- Partition index is a measure ofvalidity similar to partition coeGcient, based on using Pj = ci=1 (uij)m as a measure ofhow well the jth data point has been classi- 2ed. The closer a pixel is to a codebook entry, the
trickl-cluster-master
- java FCM program it contain classes of clustering with fuzzy c means algorithm in java -java FCM program it contain classes of clustering with fuzzy c means algorithm in java
FCM
- 使用模糊C均值聚类（FCM）的方法对状态进行分类，其优点首先是可以根据实际情况自动确定聚类中心，减少人工干涉的因素，其次，对状态特征参数不是进行硬分类，而是通过隶属度的表征方式对其聚类，更加符合现实状态类别之间不具备明显界限的实际问题。(The use of fuzzy C mean clustering (FCM) method to classify the state, its advantage is first can aut