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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: 数据挖掘中K均值算法的实现用MATLAB编写-data mining to the K-means algorithm to achieve prepared using MATLAB
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Size: 1024 |
Author: 方巍巍 |
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Description: k-means算法(matlab编写),其中包含测试数据集,可以使用.-This is a k-means algorithm(in matlab) contains data set which can be used
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Size: 18432 |
Author: hu min |
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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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Size: 1024 |
Author: 阿兜 |
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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: 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: 数据挖掘中模糊k均值算法，matlab工具编写。-data mining fuzzy k-means algorithm, Matlab tool for the preparation.
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Size: 4096 |
Author: 明文 |
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Description: K-均值算法的Matlab源代码，比较简短-Matlab source code of K-means algorithm
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Size: 1024 |
Author: luo |
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Description: k均值聚类算法源码
聚类算法学习的实例功能-k-means cluster algorithm
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Size: 3072 |
Author: wueching |
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Description: K-mean均值算法的matlab功能实现-K-means to achieve the matlab function
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Size: 55296 |
Author: spinach |
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Description: k-means算法的实现，实用matlab是实现的，可以用啦做聚类分析-k-means algorithm for the realization of the practical realization of matlab, so you can use cluster analysis
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Size: 51200 |
Author: test |
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Description: K-means MATLAB源程序，适用于聚类分析的代码-K-means MATLAB programe
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Size: 7168 |
Author: 黄小成 |
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Description: 对于灰度图的 k均值算法实现 matlab代码-Gray graphics k-means matlab code
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Size: 1024 |
Author: Leo |
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Description: 聚类方法中的K-means实现，用matlab语言实现的聚类-Clustering of K-means implementation of the cluster with matlab language
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Size: 153600 |
Author: 收到回复 |
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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.
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Size: 2048 |
Author: 郑馨 |
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Description: k均值，数据已经有了，主要用于分类，美列都是一类数据，只用了其中一部分，数据是自己编的。(K mean, data already exists, mainly for classification, the United States column is a kind of data, only a part of the data is their own series.)
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Size: 8192 |
Author: guanyu
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Description: K-means算法 matlab 确保运行成功(K-means matlab successful)
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Size: 2048 |
Author: 大猩猩97
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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.)
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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.)
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Size: 1024 |
Author: invoker`Z |
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Description: k-means算法主程序，已经经过测试，具体参数需要自己调整(K-means algorithm for matlab)
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Size: 1024 |
Author: 水蒸汽12345 |
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