Description: Matlab环境下的k-means聚类算法，实现图像分割，很快阿！-K-means Clustering arithmetic based on Matlab platform.It s fast for Image-Division! Platform: |
Size: 32768 |
Author:刘明霞 |
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Description: 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! Platform: |
Size: 32768 |
Author:HaicoLi |
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Description: k均值聚类的动态分类算法 灰度图和彩图的
-k-means clustering algorithm for the dynamic classification of grayscale and color Platform: |
Size: 3072 |
Author:zhangyan |
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Description: 现有的几个网络拓扑随机发生器，其实很难生成理想的网络拓扑结构，其主要原因在于很难控制节点的疏密和间距。我们提出来的这个改进算法，在随机抛撒节点的时候使用了K均值聚类，由本算法作为网络拓扑发生器，网络节点分布均匀且疏密得当，边的分布也比较均衡-The few existing random network topology generator, is in fact very difficult to generate the desired network topology, the main reason it is difficult to control the node density and spacing. We put forward the improved algorithm, throw in random nodes when using the K-means clustering, by the algorithm as a network topology generator, network nodes and spacing evenly distributed properly, the edge of a more balanced distribution of Platform: |
Size: 2048 |
Author:ben |
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Description: 这是一个关于k中心聚类的算法，希望大家指点。-It is a clustering algorithm k centers, I hope everyone pointing. Platform: |
Size: 593920 |
Author:fanliutong |
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Description: 基于MATLAB的k-means算法 较好的解决了图像分类聚类的问题-MATLAB based on the k-means algorithm better solved the problem of image classification clustering Platform: |
Size: 1024 |
Author:刘小强 |
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Description: 空间数据分析中最常用的是聚类分析,而K-MEANS算法是聚类分析中常用的,其主要思想是在给定的聚类数目下对多维(我做的是三维空间点)向量进行聚类,-Spatial data analysis is the most commonly used cluster analysis, while the K-MEANS algorithm is commonly used in cluster analysis, the main idea is to set the number of under the multi-dimensional clustering (I make the three-dimensional space-point) vector cluster, Platform: |
Size: 6144 |
Author:tangkezong |
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Description: matlab源码关于模糊K均值聚类算法，很好的，适合大家下载研究学习-matlab source code on the fuzzy K-means clustering algorithm, very good for everyone to download research study Platform: |
Size: 1024 |
Author:亨利 |
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Description: 基于matlab的K均值聚类程序。其中用IRIS数据进行验证，得到了很好的结果。文件中包含了演示后的结果图-Matlab-based K-means clustering procedure. Which use IRIS data verification, have had good results. File contains the results of the demonstration plan Platform: |
Size: 32768 |
Author:wanghuali |
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Description: 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 Platform: |
Size: 5120 |
Author:chunxiao |
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Description: K-均值聚类算法，对数据进行聚类分析，可用于提取关键帧等。用matlab实现-K-means clustering algorithm, cluster analysis of data that can be used, such as key frame extraction. Using matlab to achieve Platform: |
Size: 122880 |
Author:zhengmin |
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Description: 模式识别c均值聚类，也陈k均值，是模式识别中最最要的聚类方法之一。-Pattern Recognition, c-means clustering, and Chen k means, is far the most to the clustering pattern recognition methods. Platform: |
Size: 118784 |
Author:连 |
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Description: 典型的K均值聚类方法，用matlab编写，有几个文件，大家可以参考参考。-K-means clustering methods typically used matlab write, there are several files, you can refer to the reference. Platform: |
Size: 2048 |
Author:郑馨 |
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Description: K-means算法是硬聚类算法，是典型的基于原型的目标函数聚类方法的代表，它是数据点到原型的某种距离作为优化的目标函数，利用函数求极值的方法得到迭代运算的调整规则。K-means算法以欧式距离作为相似度测度，它是求对应某一初始聚类中心向量V最优分类，使得评价指标J最小。算法采用误差平方和准则函数作为聚类准则函数。(The K-means algorithm is a hard clustering algorithm, which is representative of the prototype based objective function clustering method. It is the distance from the data point to the prototype as the objective function of the optimization, and the method of using the function to find the extremum is used to get the adjustment rules of the iterative operation. The K-means algorithm takes Euclidean distance as the similarity measure, it is to find the V optimal classification corresponding to an initial cluster center vector, so that the evaluation index J is the smallest. The error square sum criterion function is used as a clustering criterion function.) Platform: |
Size: 1024 |
Author:Daizy7 |
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Description: K-means聚类算法的matlab实现(k-means clustering is a method of vector quantization, originally from signal processing, that is popular for cluster analysis in data mining. k-means clustering aims to partition n observations into k clusters in which each observation belongs to the cluster with the nearest mean, serving as a prototype of the cluster. This results in a partitioning of the data space into Voronoi cells.) Platform: |
Size: 1024 |
Author:invoker`Z |
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