This tool implements the KMeans clustering algorithm on a point layer, assigning each point to the nearest cluster as defined.
The Cluster KMeans tool can be selected by navigating the following path:
Tools > Vector Processing > Spatial Analysis > Cluster KMeans
The first section requires you to select required data layers and parameters to run the Cluster KMeans tool.
- Select a Point Layer - Layer on which you will run this tool.
- Number Of Clusters - Total number of clusters that should be produced by the KMeans clustering algorithm over the dataset.
The second section requires you to select the range of data for the operation to be implemented. There are two options available:
- Select By Graphics
- All Data
For more information about these options and how to implement them, see Data Selection Methods.
The output point layers contains Cluster ID and Cluster Size. Every single point will be assigned a cluster ID based on the number of clusters. Cluster Size indicates the number of points in Cluster ID.
You can view the output after storing it. To save the output, you must enter the Output Layer Name and click on Save Data button. The saved output will be added as a new layer in the current map session, where you can apply styling as required. This output layer will also be available in 'My Data' section and can be used in any map session of interest.