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K-均值聚类算法 vc++图形演示程序-K-means clustering algorithm c++ demo program
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K均值聚类算法，取前k个点为初始聚类中心，然后进行迭代聚类-K means clustering algorithm, fetch the first k points as initial cluster centers, then the iterative clustering
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基于k-means的文本聚类程序实现，希望对大家有帮助！-Based on the k-means clustering procedures for the realization of the text, I hope all of you help!
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简单实用的k均值聚类算法，可以实现多位向量的简单聚类-Simple and practical k-means clustering algorithm, can achieve more than a simple vector clustering
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用于图像处理，K-MEANS聚类实现图像的分割和识别，是一种重要的图像处理方法-For image processing, K-MEANS Clustering achieve image segmentation and recognition, is an important image processing method
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用VC写的关于k-mean聚类算法的程序。-Written by VC on the k-mean clustering algorithm procedure.
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k means clustering algorithm used for clustering a spread data
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k-means clustering algorithm, C means Fuzzy clustering algorithm-k-means clustering algorithm, C means Fuzzy clustering algorithm...
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K-means聚类算法实现代码，在VC++环境下开发的，令附有实验样本集。-K-means clustering algorithm code, in the VC++ development environment, so that experiments with sample set.
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k-mean clustering Matlab M-file
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k均值聚类算法，可以完成k均值聚类运算。实现几个点的聚类-k means clustering algorithm, k means clustering operation can be completed. Clustering to achieve several points
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K-means算法的聚类分析 Visual basic版本-K-means Clustering
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k均值聚类算法,初始随机给定k个簇中心，根据邻近原则，把待分类的样本点分到各个簇。-k-means clustering algorithm,which is applied in RBF neural network.
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k-均值聚类算法C语言源码,k-均值聚类算法C语言源码-k-means clustering algorithm C language source code
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基于vc程序的实现K-Means动态聚类算法源程序-K-Means clustering algorithm based on vc program source code implementation of K-Means clustering algorithm based on vc program source code to achieve
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New revised K-means聚类算法，为matlab函数，需要调用才能使用-New revised K-means clustering algorithm for matlab function, you need to call in order to use
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在里面的的是一些关于k-means的东西，用的mnist数据(I try the Mnits data and use K-means to doing the clustering)
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利用所编的程序，完美的实现经典的K-means聚类算法分析。(Using the program compiled, the classic K-means clustering algorithm is realized perfectly.)
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随机生成1000个二维坐标点并用K-means算法计算聚类结果(1000 two-dimensional coordinate points are generated randomly and the clustering results are calculated by K-means algorithm)
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介绍了k-means 均值聚类，能很好的将离散的点，聚类成几个指定的聚合点。(The K-means mean clustering is introduced, and the discrete points can be well clustered into several designated aggregation points.)
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