  We introduce the interactive tool pandemonium to cluster model predictions
that depend on a set of parameters. The model predictions are used to define
the coordinates in observable space which go into the clustering. The results
of this partitioning are then visualized in both observable and parameter space
to study correlations between them. The tool offers multiple choices for
coordinates, distance functions and linkage methods within hierarchical
clustering. It provides a set of diagnostic statistics and visualization
methods to study the clustering results in order to interpret the outcome. The
methods are most useful in an interactive environment that enables exploration,
and we have implemented them with a graphical user interface in R. We
demonstrate the concepts with an application to phenomenological studies in
flavor physics in the context of the so-called B anomalies.
