matlab kmeans
时间: 2023-08-28 13:07:52 浏览: 33
K-means是一种聚类算法,MATLAB中有内置函数`kmeans`可以实现K-means聚类。
下面是一个简单的例子:
```matlab
data = rand(100,2); %生成随机数据
k = 3; %聚类数
[idx, C] = kmeans(data, k); %聚类
scatter(data(:,1), data(:,2), 10, idx, 'filled'); %画出聚类结果
hold on
plot(C(:,1), C(:,2), 'kx', 'MarkerSize', 15, 'LineWidth', 3); %标出聚类中心
```
在这个例子中,`data`是一个100行2列的随机矩阵,`k`是要聚类的数目。`kmeans`函数返回聚类结果`idx`和聚类中心`C`。最后用`scatter`函数画出聚类结果,用`plot`函数标出聚类中心。
你可以根据你的数据类型和聚类需求调整这个例子。
相关问题
Matlab kmeans
K-means clustering is a popular clustering algorithm used in data science and machine learning. It is a type of unsupervised learning where the algorithm tries to group similar data points together.
In Matlab, the kmeans function is used to perform k-means clustering. The function takes in a dataset and the number of clusters required as input. The output of the function is the cluster indices for each data point and the centroids of each cluster.
Here is an example code for performing k-means clustering in Matlab:
```matlab
% Load data
load fisheriris
% Perform k-means clustering
[idx, C] = kmeans(meas, 3);
% Plot the clusters
gscatter(meas(:,1), meas(:,2), idx)
hold on
plot(C(:,1), C(:,2), 'kx', 'MarkerSize', 15, 'LineWidth', 3)
legend('Cluster 1','Cluster 2','Cluster 3','Centroids','Location','NW')
```
In this example, the fisheriris dataset is loaded and k-means clustering is performed with 3 clusters. The indices of the clusters and the centroids are stored in the 'idx' and 'C' variables respectively. Finally, the clusters are plotted using the 'gscatter' function and the centroids are plotted using the 'plot' function.
matlab kmeans代码
可以给你提供一份简单的Matlab Kmeans代码,可以实现对数据进行聚类分析。你需要提供数据和指定聚类数量。以下是代码:
x = YourData; % Your data
n = NumberOfClusters; % Number of clusters you want to obtain
[idx,C] = kmeans(x, n); % k-means algorithm
% idx contains the cluster index of each observation
% C contains the centroid locations
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