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Description: 動態聚類k-means演算 將輸入在程式中的數據資料 給予適當的分群-dynamic clustering k-means figure:proper hiving off of input datum in programme
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Size: 829440 |
Author: 傅國欽 |
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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: matlab程序，用于人脸识别的K均值算法程序，非常有用。-matlab program for K-means algorithm for face recognition program, very useful.
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Size: 3072 |
Author: laosee |
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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
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Size: 2048 |
Author: ben |
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Description: knn 方法为k均值聚类用于数据点的分类-KNN method for k-means clustering for the classification of data points
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Size: 27648 |
Author: |
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Description: 聚类算法：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。 这里是MAtlab源代码。-err
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Size: 9216 |
Author: 烈马 |
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Description: 一个刚编出来的K—means 聚类算法的matlab源代码 适合多维数据-Just made out of a K-means clustering algorithm matlab source code for multi-dimensional data
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Size: 1024 |
Author: 吴立锋 |
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Description: matlab 代码 k-means 算法 实现2－D数据的聚类-matlab code for k-means algorithm is 2-D data clustering
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Size: 2048 |
Author: 王新民 |
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Description: 用matlab7.0编写的k均值算法，参数可调节，很好用-K-MEANS MATLAB
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Size: 19456 |
Author: ghw |
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Description: The number of states in GMM as the generative model of the frames is obtained using
k-means algorithm. This also helps to initialize the mean vector and the covariance
matrix of the individual state of the GMM. The training LPC frames collected from
three speech segments are subjected to PCA for dimensionality reduction and are
subjected to k-means algorithm. The total number of frames is equal to the total
number of vectors that are subjected to k-means clustering.
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Size: 728064 |
Author: Khan17
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