Setting up and running Unsupervised Classification

With an unsupervised classification, training samples are not required. This classification is performed on the selected attributes to find data clusters.

To set up and run an unsupervised classification

In the Object Analyst window, in the list under Operation, select Unsupervised Classification.
The display is refreshed to show the settings for unsupervised classification.
Under Vector Layer and Fields, click Select, and then in the Vector Layer and Field Layer Selection window, do the following:
1. In the File box, type or select the file you want.
  If the file you want does not appear in the list, click Browse, and then select the file you want.
2. In the Layer box, type or select the layer you want.
3. In the Fields box, click one or more of the fields you want or, to select all the fields, click Select All.
  A check mark appears beside each field you select.
4. Click OK.
Under Output Class Field, type a name for a field to create during processing.
The field you specify will be added to the attribute table of the selected layer to store the predicted results of the classification, which you can then view in Attribute Manager. Whenever you run a classification subsequently with this field specified, the existing value will be overwritten.
Under Classifier, in the Clusters box, type or select the number of clusters to use as input for the k-means algorithm.
Do one of the following:
- To add the operation to the Process Canvas box, click Add.
- To add the operation to the canvas and run the process, click Add and Run.