One way of validating the results of clustering and finding the right number of clusters to display in the map is to compare the results of cluster analysis to multidimensional scaling. This can be done in the view Discrete clustering - cluster validation in Gabmap. A cluster map is displayed, and under the map, there is a plot which is the same two-dimensional MDS plot which you find at Multidimensional scaling - mds plots. The plot is colored according to the chosen cluster analysis, so that you can compare the clustering results with the results of MDS. The plot helps you to see how well separated the clusters are.
You can change clustering method and number of clusters under the plot. You can also choose to display only some of the clusters in the plot in order to inspect the separation between or within these clusters more closely.
The black dots in the map indicate the cluster center, that is the place which is most typical for each cluster. The numbers indicate outliers in each cluster. The outliers are found at the outskirts of each cluster cloud in the plot.
If no clear, separated clouds of dots can be identified in the plot, the data set is probably truly continuous and it does not make sense to use cluster analysis.