Pattern analysis

Since version 8.1

Pattern analysis helps you understand how a target variable's states differ from each other.


For example, you might be interested in the difference between those who purchased a product and those who did not, or you might be interested in how one US state differs from others. You could also use pattern analysis to understand the different clusters (latent states) in a cluster model (mixture model).

Auto insight summary

The auto-insight summary tab, provides discrimination information between a discrete or continuous target state and the other states of the same variable.

The image below, demonstrates the tool on the 'Simpson's Paradox' example network included with Bayes Server. It clearly shows that 'Department' is the key discriminator of 'Admittance'.

Pattern analysis

Auto insight outputs

Auto insight information is output for each state t of the target variable. (discretized states if the target is continuous). Target states are ordered based on the maximum strength found over the test variables.

Auto insight options

Pattern analysis continuous