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matlab源代码实现快速kmeans聚类
Date : 2010-09-19 Size : 3.9kb User : shiziw369

数据挖掘中k-means聚类算法的实现源代码-clustering algorithm source code in data mining
Date : Size : 3kb User : 张乐

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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)
Date : Size : 1kb User : 阿兜

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一个基于K均值聚类的RBF神经网络,注释写的很明白,有不明白的地方可以发邮件问我。-a K-means clustering based on the RBF neural network, notes written very well, did not understand the local mail can ask me.
Date : Size : 2kb User : bruce

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自己做的一个kmean聚类程序,里面有例子和聚类程序 -Their clustering kmean to do a procedure, there are examples and clustering procedures
Date : Size : 3kb User : maweilin

这是一个关于K均值的聚类算法希望对大家有用-This is a study on K-means clustering algorithm to all of us hope that useful
Date : Size : 7kb User : 王林

数据挖掘算法很多,其中模糊k均值算法是目前使用比较多的分类方法-Many data mining algorithms, including fuzzy k-means algorithm is currently using a relatively large number of classification methods
Date : Size : 3kb User : 张云

改进的k均值算法,可以加速运行时间,详见Using the Triangle Inequality to Accelerate k-Means-Improved k-means algorithm, can accelerate the running time, see Using the Triangle Inequality to Accelerate k-Means
Date : Size : 13kb User : xz

k-means算法,请大家参考,这是一个新的k-means源码-k-means algorithm, please refer to, this is a new source of k-means
Date : Size : 81kb User : fanliutong

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cskmeans 聚类算法的一种 1. 分裂法(partitioning methods):给定一个有N个元组或者纪录的数据集,分裂法将构造K个分组,每一个分组就代表一个聚类,K<N。而且这K个分组满足下列条件:(1) 每一个分组至少包含一个数据纪录;(2)每一个数据纪录属于且仅属于一个分组(注意:这个要求在某些模糊聚类算法中可以放宽);对于给定的K,算法首先给出一个初始的分组方法,以后通过反复迭代的方法改变分组,使得每一次改进之后的分组方案都较前一次好,而所谓好的标准就是:同一分组中的记录越近越好,而不同分组中的纪录越远越好。使用这个基本思想的算法有:K-MEANS算法、K-MEDOIDS算法、CLARANS算法;
Date : Size : 1kb User : lance

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kmeans algoritmo for user to use
Date : Size : 90kb User : nieradka

Radial Basis Function Network using K-means algorithm
Date : Size : 23kb User : Bomberino

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background subtraction using kmeans and gmm
Date : Size : 7kb User : priya0803

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可以实现K均值聚类的MATLAB程序。但是有点小问题。(The MATLAB program of K mean clustering can be realized.)
Date : Size : 16kb User : southpole

k-means算法实现以及Iris数据集(Implementation of K-means algorithm and Iris data set)
Date : Size : 1kb User : 二胡二胡

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用matlab 实现了kmeans算法还附有评价指标计算(Matlab to achieve kmeans algorithm also attached to the evaluation index calculation)
Date : Size : 2.35mb User : 呆子哥哥

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)
Date : Size : 28kb User : 麻衣蚂蚁

matlab实现图像变化检测 分别用kmeans fcm flicm实现图像的变化检测(image change detetion by kmeans,fcm,flicm)
Date : Size : 1.42mb User :

KNN Kmeans RBF Algorithm based on matlab
Date : Size : 506kb User : LIZHAOYANH

该课题为基于kmeans的聚类分割,输入一张彩色图像,可以选择需要分割成多少类,就会以不同颜色区分不同的块,带有GUI界面,操作丰富。(This topic is based on Clustering Segmentation of kmeans. Input a color image, you can choose how many categories you need to segment, and then different blocks will be distinguished with different colors, with GUI interface and rich operation.)
Date : Size : 71kb User : for Matlab
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