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Understanding Clusters Profiles
The screen Cluster Profiles can be brOKen down into three parts:


In the upper part, a drop-down list allows you to select the variable for which you want to see the cross
statistics. Variables are presented in descending order of the significance of their contribution relative to
the target category of the target variable. When a cluster is selected, the variables visible in the
drop-down list are sorted according to the difference between their cluster profile and their population
profile (the Kullback-Leibler divergence is used to measure this difference). The variable that appears
first on the list is the variable exhibiting the greatest difference between its two profiles. This sorted list of
variables provides the set of discriminatory variables required to describe a cluster.
In the middle part, a table presents each cluster in a summarized fashion.
Column …
Indicates…
For instance…
Cluster
Name
The name of the cluster
Cluster 1
Frequencies The number of observations contained in The customers contained in cluster 1 represent 4.22% of the
the cluster relative to the total number of total number of customers contained in your entire training
observations contained in the data set
data set
% of '1'
The proportion of observations
51.17% of the customers contained in cluster 1 belong to the
contained in the cluster belonging to the target category of the target variable Class. In other words,
target category of the target variable
51.17% of the customers contained in this cluster responded
in a positive manner to the test phase of your marketing
campaign
This table allows you to select the cluster for which you want to view cross statistics.
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SAP InfiniteInsight® 7.0
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