聚类分析matlab 代码
时间: 2023-09-15 12:22:06 浏览: 43
Sure! Here is a sample code for performing clustering analysis using MATLAB:
```matlab
% Load the data
data = load('your_data_file.mat'); % Replace 'your_data_file.mat' with your actual data file
% Perform clustering analysis
numClusters = 3; % Set the desired number of clusters
eva = evalclusters(data, 'kmeans', 'silhouette', 'KList', 1:numClusters);
% Get the cluster labels
clusterLabels = eva.OptimalY;
% Plot the data with cluster colors
gscatter(data(:,1), data(:,2), clusterLabels);
```
In this code, you would need to replace `'your_data_file.mat'` with the actual file name or path to your data file. The `numClusters` variable determines the desired number of clusters. The code uses the `evalclusters` function with the `'kmeans'` clustering algorithm and the `'silhouette'` criterion to evaluate the optimal number of clusters. Finally, it generates a scatter plot of the data with each point colored according to its assigned cluster.
Make sure to have your data in the right format (e.g., a matrix or a table) before using this code. You can also explore other clustering algorithms and criteria available in MATLAB based on your specific requirements.