DATA CLASSIFICATION BY KERNEL DENSITY SHAPE INTERPOLATION OF CLUSTERS

A data processing system is provided that comprises a processor, a random access memory for storing data and programs for execution by the processor, and computer readable instructions stored in the random access memory for execution by the processor to perform a method for obtaining a shape interpolated representation of shapes of clusters in an image of a clustered dataset. The method comprises generating a density estimate value of each grid point of a set of grid points sampled from the image at a specified resolution for each cluster using a kernel density function; evaluating the density estimate value of each grid point for each cluster to identify a maximum density estimate value of each grid point and a cluster associated with the maximum density estimate value; and adding each grid point for which the maximum density estimate value exceeds a specified threshold to the associated cluster to form a shape interpolated representation.