Data Mining Techniques for Segmentation - Data Mining Techniques in CRM: Inside Customer Segmentation - page 97

Figure 3.11 IBM SPSS Modeler recommended Kohonen Model options.
COHESION OF THE CLUSTERS
A good clustering solution is expected to be composed of dense concentrations of
records around their centroids. Large dispersion values indicate non-homogeneous
groupings and suggest further partitioning of the dataset. A number of useful
statistics can be calculated to summarize the concentration and the level of internal
cohesion of the revealed clusters such as:
• Standard deviations and pooled standard deviations of the clustering fields.
Data miners should start by examining the standard deviations of the clustering
fields for each cluster, hoping for small values which indicate a small degree of
dispersion. The pooled standard deviation of a clustering field is the weighted
(according to each cluster's size) average of the individual standard deviations
for all clusters. Once again we anticipate low variability and small values which
denote increased cohesion.