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) Platform: |
Size: 1024 |
Author:阿兜 |
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Description: 均值为K的聚类算法,是一种对聚类数据进行的最简单的算法,广泛应用在各种场合中。-K mean clustering algorithm for clustering data is the most simple algorithm, widely used in various occasions. Platform: |
Size: 48128 |
Author:sunjianqing |
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Description: 程序是基于K均值聚类的RBF代码,很好的一个例子。-K means clustering procedure is based on the RBF code, a good example. Platform: |
Size: 1024 |
Author:唐毅 |
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Description: K-means算法是很典型的基于距离的聚类算法,采用距离作为相似性的评价指标,即认为两个对象的距离越近,其相似度就越大(K-means algorithm is a typical distance based clustering algorithm. The distance is used as the evaluation index of similarity, that is, the closer the distance between the two objects, the greater the similarity) Platform: |
Size: 13312 |
Author:venshow
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Description: 介绍了传统的图像分割与K-均值聚类算法分割,然后利用OpenCV函数将其实现,并介绍了OpenCV中图像分割相关的基本函数。(This paper introduces the segmentation of traditional image segmentation and K- mean clustering algorithm, then uses OpenCV function to implement it, and introduces the basic functions of image segmentation in OpenCV.) Platform: |
Size: 464896 |
Author:术道
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Description: 用VC++写的K均值聚类算法,可以直接使用(K mean clustering algorithm is written by VC++ , which can be used directly.) Platform: |
Size: 187392 |
Author:gongshixin
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Description: 利用MATLAB实现K均值聚类算法,加深对该算法的理解。(We use MATLAB to achieve K mean clustering algorithm to deepen our understanding of the algorithm.) Platform: |
Size: 5120 |
Author:WG_JNU |
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