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Description: MATLAB编写的一种模式识别里的重要的模糊聚类方法K-means算法的matlab程序.-MATLAB prepare a Pattern Recognition's important Fuzzy clustering methods K-means algorithm Matlab procedures.
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Author: zs |
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Description: MATLAB 数据挖掘算法，fuzzy-K-means聚类算法源代码，用于模糊聚类分析-MATLAB data mining algorithms, fuzzy-K-means clustering algorithm source code, Fuzzy clustering analysis for the
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Size: 1180 |
Author: puxx |
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Description: 关于k-means聚类算法的MATLAB实现
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Size: 10178 |
Author: chen |
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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
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Size: 1005 |
Author: 刘小强 |
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Description: 数据挖掘中k-means聚类算法的实现源代码-clustering algorithm source code in data mining
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Size: 3072 |
Author: 张乐 |
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Description: 基于划分的聚类分析算法k-means,主要用于数据挖掘领域.-Partition- based cluster analysis algorithm k-means, used mainly for data mining areas.
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Size: 3072 |
Author: 许朝 |
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Description: 实现聚类K均值算法： K均值算法：给定类的个数K，将n个对象分到K个类中去，使得类内对象之间的相似性最大，而类之间的相似性最小。 缺点：产生类的大小相差不会很大，对于脏数据很敏感。 改进的算法：k—medoids 方法。这儿选取一个对象叫做mediod来代替上面的中心 的作用，这样的一个medoid就标识了这个类。步骤： 1，任意选取K个对象作为medoids（O1,O2,…Oi…Ok）。 以下是循环的： 2，将余下的对象分到各个类中去（根据与medoid最相近的原则）； 3，对于每个类（Oi）中，顺序选取一个Or，计算用Or代替Oi后的消耗—E（Or）。选择E最小的那个Or来代替Oi。这样K个medoids就改变了，下面就再转到2。 4，这样循环直到K个medoids固定下来。 这种算法对于脏数据和异常数据不敏感，但计算量显然要比K均值要大，一般只适合小数据量。-achieving K-mean clustering algorithms : K-means algorithm : given the number of Class K, n will be assigned to target K to 000 category, making target category of the similarity between the largest category of the similarity between the smallest. Disadvantages : class size have no great difference for dirty data is very sensitive. Improved algorithms : k-medoids methods. Here a selection of objects called mediod to replace the center of the above, the logo on a medoid this category. Steps : 1, arbitrary selection of objects as K medoids (O1, O2, Ok ... ... Oi). Following is a cycle : 2, the remaining targets assigned to each category (in accordance with the closest medoid principle); 3, for each category (Oi), the order of selection of a Or, calculated Oi Or replace the consumption-E (Or)
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Author: 阿兜 |
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Description: 数据挖掘算法，K-means聚类算法源代码，用于聚类分析-data mining algorithms, K-means clustering algorithm source code for the cluster analysis
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Size: 1024 |
Author: sah |
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Description: 模式识别一份很好的作业,包括线性分类器；最小风险贝叶斯分类器；监督学习法分层聚类分析；K－L变换提取有效特征,支持向量机-a very good operation, including linear classification; Minimum risk Bayesian classifier; Supervised learning method Hierarchical clustering analysis; K-L transform effective features, support vector machines
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Size: 2599936 |
Author: 郭攀红 |
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Description: 分类聚合算法k-means的实现,用matlab-polymerization classification algorithm k-means the realization of using Matlab
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Size: 1024 |
Author: 利军 |
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Description: 数据挖掘常用的算法，包括id3，k均值，FCM，SVM,CART五个常用的算法，是用matlab编写的。-commonly used data mining algorithms, including id3, k mean, FCM, the SVM, CART five commonly used algorithm is the use of Matlab prepared.
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Size: 18432 |
Author: 李冬宾 |
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Description: 实现聚类K均值算法： K均值算法：给定类的个数K，将n个对象分到K个类中去，使得类内对象之间的相似性最大，而类之间的相似性最小。-achieving K-mean clustering algorithms : K-means algorithm : given the number of Class K, n objects assigned K to 000 category, making such objects within the similarity between the largest category of the similarity between the smallest.
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Size: 1024 |
Author: yili |
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Description: 模糊核聚类及几篇文章，用于数据和图像的模糊聚类分割，效果还行-nuclear fuzzy clustering and articles for data and image segmentation fuzzy clustering, the results were OK
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Size: 1381376 |
Author: 张莉 |
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Description: Test k-means on 2-D data
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Size: 2048 |
Author: 黎思 |
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Description: 对于模式识别中的k均值（也称c均值）问题，给出了matlab实现。-pattern recognition for the k-means (also called c-means), is the realization of Matlab.
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Size: 2048 |
Author: slyang |
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Description: 基于matlab的图像K均值聚类算法程序 -Matlab-based Image K-means clustering algorithm procedures
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Size: 1024 |
Author: 卫 |
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Description: K近邻法的matlab程序，发现大家都在找它！-K-nearest neighbor method of Matlab procedures, I found that we all have to find it!
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Size: 2048 |
Author: wang |
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Description: ％ 信道容量C的迭代算法 ％
％ 函数说明： ％
％ [CC,Paa]=ChannelCap(P,k) 为信道容量函数 ％
％ 变量说明： ％
％ P：输入的正向转移概率矩阵，k：迭代计算精度 ％
％ CC：最佳信道容量，Paa：最佳输入概率矩阵 ％
％ Pa：初始输入概率矩阵，Pba：正向转移概率矩阵 ％
％ Pb：输出概率矩阵 ％
％ C：初始信道容量， r：输入符号数，s：输出符号数 ％- Channel capacity C of the iterative algorithm Function Description: [CC, Paa] = ChannelCap (P, k) for the channel capacity function Variable Description: P: input positive transition probability matrix, k: iterative calculation accuracy CC: the best channel capacity, Paa: optimal input probability matrix Pa: initial input probability matrix, Pba: positive transition probability matrix Pb: output probability matrix C: initial channel capacity, r: the number of input symbols, s: output symbol number
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Size: 1024 |
Author: |
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Description: 基于改进人工蜂群算法的K均值聚类算法-喻金平-郑杰-梅宏标，matlab(K-means clustering algorithm based on improved artificial bee colony algorithm-Yu Jinping-Zheng Jie-Mei Hongbiao, matlab)
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Size: 57344 |
Author: 辣条青年 |
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Description: 利用K均值聚类对鸢尾花样本进行聚类的matlab程序，包含源代码、样本数据、聚类结果(The matlab program of clustering iris samples by K-means clustering, including source code, sample data and clustering results)
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Size: 28672 |
Author: 麻衣蚂蚁 |
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