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 Platform: |
Size: 18432 |
Author:hu min |
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Description: 图像集群（Image Clustering）
(1)图像读入，显示图像所在路径；
(2)采用imgcluster函数进行图像集群，选择集群个数后进行图像集群；
(3)运行后，在原图像上显示集群灰度图；
(4)若要显示各个集群情况，可打开【Show Clustering Image】新窗体，显示各集群类的基于原图的彩绘区域。其中非当前集群范围，则显示灰度为255的黑色。用户可点击按纽上下查看所有集群图。-image cluster (Image Clustering) (1) read into the images, Images show host path; (2) use of imgcluster function for image clusters, After the number of clusters chosen for image clusters; (3) After the operation, in the original image displayed on the gray level clusters; (4) To show that the various clusters, [Show Open Clustering Image-- new windows, showed that the cluster type based on the maximum of regional painting. Clusters of non-current range, it shows that the intensity of 255 black. Users can click on View All button next cluster map. Platform: |
Size: 113664 |
Author:mecal |
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Description: 用matlab语言写的EM(Expectation maximization)算法,用于模式分类-Matlab language used to write the EM (Expectation maximization) algorithm for pattern classification Platform: |
Size: 2048 |
Author:罗升阳 |
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Description: K-MEANS算法
输入：聚类个数k，以及包含 n个数据对象的数据库。
输出：满足方差最小标准的k个聚类。
处理流程：
（1） 从 n个数据对象任意选择 k 个对象作为初始聚类中心；
（2） 循环（3）到（4）直到每个聚类不再发生变化为止
（3） 根据每个聚类对象的均值（中心对象），计算每个对象与这些中心对象的距离；并根据最小距离重新对相应对象进行划分；
（4） 重新计算每个（有变化）聚类的均值（中心对象）-K-MEANS algorithm Input: cluster number k, and contains n data object database. Output: the minimum standards to meet the variance k-clustering. Deal flow: (1) a data object from the n choose k object as initial cluster centers (2) cycle (3) to (4) until a change in each cluster is no longer so far (3) according to each Clustering objects mean (central object), calculated for each object with these centers to object distance and in accordance with a minimum distance between a re-division of the corresponding object (4) re-calculated for each (change) clustering of the mean (central object ) Platform: |
Size: 3072 |
Author:快快 |
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Description: this a code to segment the color texture using Gabor filter. It uses the initial segmentation using kmeans clustering.-this is a code to segment the color texture using Gabor filter. It uses the initial segmentation using kmeans clustering. Platform: |
Size: 83968 |
Author:sidharth |
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Description: K-meansK均值聚类在无监督的情况下选择图像特征的算法-K-meansK means clustering in the case of unsupervised image feature selection algorithm Platform: |
Size: 46080 |
Author:renli |
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Description: 包括K-均值聚类算法的思想介绍，kmeans的MATLAB代码，c语言代码、c++代码。-Including the K-means clustering algorithm introduced the idea, kmeans of MATLAB code, c language code, c++ code. Platform: |
Size: 10240 |
Author:刘斌 |
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Description: K-means is a clustering algorithm
In the beginning we determine number of cluster K and we assume the centroid or center of these clusters. We can take any random objects as the initial centroids or the first K objects in sequence can also serve as the initial centroids.
There are two function for that the kMeanCluster and distMatrix Platform: |
Size: 2048 |
Author:Luis |
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Description: 彩色图像分割，灰常不错。This function implements kmeans clustering on an input RGB (m x n x 3)
image. The user inputs at least two inputs: IMGIN and NCLUSTERS, and this
function will step through an interactive color segmentation using kmeans clustering. It is interactive in that the user will be prompted to click-define the target colors in the segmentation.-This function implements kmeans clustering on an input RGB (m x n x 3)
image. The user inputs at least two inputs: IMGIN and NCLUSTERS, and this
function will step through an interactive color segmentation using kmeans clustering. It is interactive in that the user will be prompted to click-define the target colors in the segmentation. Platform: |
Size: 9216 |
Author:zhuweina |
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Description: 该代码能够实现K均值聚类算法对彩色图像分割，在MATLAB下实现。-The code can achieve K means clustering algorithm to color image segmentation, in MATLAB to achieve. Platform: |
Size: 1024 |
Author:牛少敏 |
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