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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均值聚类算法实现数据挖掘的matlab源代码-Fuzzy C-Means clustering algorithm for data mining matlab source code
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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 points and N is the number of coor
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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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采用模糊C均值对数据集进行聚类的matlab代码-Matlab code for data clustering based on fuzzy c-means algorithm
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FCM模糊C均值聚类资料，用matlab编程，实用-FCM fuzzy C-means clustering data, matlab programming, practical
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模糊c-均值聚类算法 fuzzy c-means algorithm (FCMA)或称（ FCM）。在众多模糊聚类算法中，模糊C-均值（ FCM） 算法应用最广泛且较成功，它通过优化目标函数得到每个样本点对所有类中心的隶属度，从而决定样本点的类属以达到自动对样本数据进行分类的目的。(Fuzzy c-means clustering algorithm or FCM. Among many fuzzy clustering algorithms, the Fuzzy C-Means algori
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