搜索资源列表
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这个是K-Means动态聚类算法的源程序，需要的请下，请多多指教，谢谢！-This is a K - Means clustering algorithm source, the need to please, please exhibitions, thank you!
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数据挖掘算法源代码 k-means聚类算法的C#代码-Source code data mining algorithms k-means clustering algorithm C# code
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本实验基于K-Means聚类算法思想实现了字符分割，因为车牌规定是7位的，所以K取7。另外本实验对K-Means算法进行了改进，充分考虑了初始点的设置及迭代结束条件。实验结果证明这种改进的K-Means算法实现车牌字符分割是快速、有效的。-In this study, K-Means clustering algorithm based on the ideology of the character segmentation, because the license plate require
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聚类K-Medoids算法。文件里面包含了详细的程序说明和示例。-K-Medoids clustering algorithm.The file contains a detailed descr iption of the procedures and examples.
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毕设题目，基于K均值的PSO聚类算法，共享了。-Bi-based topic of the PSO-based K-means clustering algorithm, shared.
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基于K-means聚类算法的社团发现方法
先定义了网络中节点关联度,并构建了节点关联度矩阵, 在此基础上给出了一种基于 K-means聚类算法的复杂网络社团发现方法。
以最小关联度原则选取新的聚类中心, 以最大关联度原则进行模式归类,直到所有的节点都划分完为止, 最后根据模块度来确定理想的社团数-K-means clustering algorithm based on the association discovery
To define a network node cor
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K-means均值聚类算法,用C语言实现
k-均值聚类算法
-Means K-means clustering algorithm, using C language realization of k-means clustering algorithm
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这是一个基于K-means的聚类算法，可用于网页信息聚类，例如电子产品的型号聚类等。-This is based on the K-means clustering algorithm, clustering can be used for website information, such as electronic products, such as the Model Cluster.
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k-means算法是基于划分的聚类方法，本算法简单，便于理解，以可视化界面的形式将结果展示出来。-k-means clustering algorithm is based on the division method, this algorithm is simple and easy to understand visual interface to the form of the results.
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k-means分群法，繁体中文版。以javascr ipt写成，网页上即可执行。自动产出结果。-k-means clustering, Traditional Chinese version. Javascr ipt written to the webpage can be executed. Auto output results.
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不同于k均值聚类的k中心聚类，2007年SCIENCE文章Clustering by Passing Messages Between Data Points 中的方法-Unlike k-means clustering of the k cluster centers, in 2007 SCIENCE article, Clustering by Passing Messages Between Data Points of the Method
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the C++ implementation of k-means for clustering
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k-means 聚类方法，用c++实现。-k-means,a method of clustering, implemented in c plus plus language.
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聚类算法：聚类分析是指事先不了解一批样品中的每一个样品的类别
基于k均值聚类学习算法的rbf神经网络实现-Clustering algorithm: cluster analysis is the prior knowledge of each batch of samples in the sample of category learning algorithm based on k means clustering of rbf neural network
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实现了一个聚类CMI算法，对给定一个数据集，按要求将其划分为三个类，并计算其分类的效率，并给出一定的结果比较及输出-It s a K-Means clustering algorithm
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关于K-means聚类的算法描述，原创，包含有大量训练和测试数据-About K-means clustering algorithm descr iption, originality, contains a large number of training and test data
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k均值聚类是最著名的划分聚类算法，由于简洁和效率使得他成为所有聚类算法中最广泛使用的。给定一个数据点集合和需要的聚类数目k，k由用户指定，k均值算法根据某个距离函数反复把数据分入k个聚类中。-K-means clustering is one of the most famous partitioning clustering algorithm, due to the simplicity and efficiency makes him become the most widely used
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实现k-means聚类算法，里面有数据可以作为测试(This file is use to achieve k-means clustering algorithm.There are data can be used as a test.)
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python实现K-means聚类算法和DBSCAN算法，都是最简单的聚类(Python implements k-means clustering algorithm and DBSCAN algorithm, which are the simplest clustering)
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k-means聚类算法的代码实现，只需要更改数据就可以实现，而且有注释，很容易懂(The code implementation of the k-means clustering algorithm can be realized only by changing the data, and there are notes that make it easy to understand)
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