kMeans Clustering

Command:

Math -> Cluster Analysis -> kMeans Clustering...

The command Math/Cluster Analysis/kMeans Clustering... (toolbar button ) allows to perform a k-means cluster analysis. The resulting cluster numbers can be assigned to the class numbers of the dataset.

How To:

Please follow these steps to perform a k-means cluster analysis: Select the variables by clicking the list of descriptors. This opens the variable selection dialog. Set the parameters of the analysis, i.e. the number of expected clusters and the scaling of the data. Click the button "Calculate" Inspect the results and click "Assign Classes" to copy the found clusters to the class numbers of the dataset. In the case you want to revert the class assignment click the undo button

Hint:

The results of the k-means procedure depend on a random initialisation, thus the may differ from run to run. If you want to find an optimum solution click the button "Optimize". This will repeat the algorithm N times and will return the best result of all runs. The optimum is condidered to be the solution with the minimum intra-cluster distance.