  This paper presents an approach to expert-guided subgroup discovery. The main
step of the subgroup discovery process, the induction of subgroup descriptions,
is performed by a heuristic beam search algorithm, using a novel parametrized
definition of rule quality which is analyzed in detail. The other important
steps of the proposed subgroup discovery process are the detection of
statistically significant properties of selected subgroups and subgroup
visualization: statistically significant properties are used to enrich the
descriptions of induced subgroups, while the visualization shows subgroup
properties in the form of distributions of the numbers of examples in the
subgroups. The approach is illustrated by the results obtained for a medical
problem of early detection of patient risk groups.
