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

Pandemonium: a clustering tool to partition parameter space -- application to the B anomalies