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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是行不通的［6］-fuzzy c-means cluster
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实现数据挖掘的几个算法，包括模糊聚类，K均值，以及K近邻等聚类算法-Some of the implementation of data mining algorithms, including fuzzy clustering, K-means, as well as neighbors, such as clustering algorithm K
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模糊Fcm代码，在matlab下开发，用c划分聚类进行数据分析-Fuzzy FCm code, developed in matlab with c divided into clustering for data analysis
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自行implement的k-mean(含fuzzy c mean)，可以直接於vc++針對大量數據進行分群的動作-Implement on its own the k-mean (with fuzzy c mean), can be directly in vc++ For clustering large amount of data movement
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采用模糊C均值对数据集data聚为cluster_n类-Fuzzy C-means data sets of data together for cluster_n category
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Fuzzy Clustering.
Problem: To extract rules from data
Method: Fuzzy c-means
Results: e.g., finding cancer cells
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利用模糊c—均值聚类方法将data 数据向量；3表示分成三类；center表示分类中心-Using fuzzy c-means clustering method to the data vector data 3 that is divided into three categories center said the classification center
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采用模糊C均值对数据集完成聚类，并得到较好的结果-Using fuzzy C means clustering on the complete data set, and get better results
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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, and its thinking that it is making is divided into the same cluster of the bigge
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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 (FCM), known as fuzzy ISODATA, is used to determine membership of each data point belongs to a cluster of a clustering algorithm level.
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模糊C-均值聚类方法的原函数，不用再进行编写，直接可以哄-the function of FUZZY C CLUSTERING
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Fuzzy clustering is a class of algorithms for cluster analysis in which the allocation of data points to clusters is not "hard" (all-or-nothing) but "fuzzy" in the same sense as fuzzy logic.
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A fault identification with fuzzy C-Mean clustering
algorithm based on improved ant colony algorithm (ACA) is
presented to avoid local optimization in iterative process of
fuzzy C-Mean (FCM) clustering algorithm and the difficulty in
fault cl
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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 is relatively simple steps, fuzzy C-means clustering (FCM), known as fuzzy ISODATA, is used to determine the membership of each data poi
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这是模糊C均值的matlab源程序，只要输入原始数据就可以按要求井陉分类~-This is the fuzzy C-means matlab source, as long as the original input data required Jingxing Category ~
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k均值算法是模式识别的聚分类问题，采用模糊C均值对数据集data聚为cluster_n类 -k-means algorithm is a pattern recognition poly classification,by using Fuzzy C-Means data sets, data gathered cluster_n class
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用于高维数据或者多维图像的模糊C均值聚类算法-Used for army fuzzy c-means clustering high-dimensional data
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该算法引入遗传算法对模糊c均值算法进行改进，并在iris数据集中进行实验验证，得到很高的正确率。-The algorithm genetic algorithm fuzzy c-means algorithm is improved, and focus on experiments in the iris data to obtain a high accuracy.
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基于fuzzy c-means（FCM）的无监督模糊聚类算法，输出值有：各个样本的类别标签、目标函数在每次迭代后的值、聚类中心以及聚类区间。内有测试数据data.mat，点击 test.m 可以完美运行。(The unsupervised fuzzy clustering algorithm based on fuzzy c-means (FCM) outputs the class labels of each sample, the value of the target function
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Fuzzy c-means (FCM) is a method of clustering which allows one piece of data to belong to two or more clusters
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