International Business Machines Corporation
Data insight discovery using a clustering technique

Abstract:

Disclosed aspects relate to data insight discovery using a clustering technique. A set of data may be compressed based on a set of proximity values with respect to a set of predictors to assemble a set of sub-clusters. A set of subgroups may be established by merging a plurality of individual sub-clusters of the set of sub-clusters using a tightness factor. A subset of the subgroups may be selected based on a selection criterion. A set of insight data which indicates a profile of the subset of the set of subgroups with respect to the set of data may be compiled for the subset of the set of subgroups.