- In the NumClusters syntax element, specify multiple values.
For example, NumClusters (3, 3, 4) fits 3 models, two with 3 clusters and one model with 4 clusters. It is good practice to try multiple initializations when fitting KModes, which is why you might use the same number more than once.
- Use the RandomSample function to select multiple sets of rows from the input data table, and use these randomly selected samples as seeds in the KModes function.
Create a table from a call to RandomSample. Give the NumSample syntax element a set of values x1, x2, …, xn where n is the number of different sets of rows to create (this becomes the number of models later created by KModes) and xi is the number of seed rows to select for each model (this determines the number of clusters in model i later created by KModes). The table column set_id identifies each set of points.
Call KModes, giving the InitialSeedTable syntax element that name of the table you created and specifying ModelIDColumn ('set_id').
You can create multiple models and compare their metrics to find the best model. There are two ways to create multiple models simultaneously: