Method for data classification by kernel density shape interpolation of clusters
AssigneeInternational Business Machines Corporation
InventorsTanveer Syeda-Mahmood, Peter J. Haas, John M. Lake, Guy M. Lohman
Life of this patent
Estimating the term…
Loading patent…
AssigneeInternational Business Machines Corporation
InventorsTanveer Syeda-Mahmood, Peter J. Haas, John M. Lake, Guy M. Lohman
Estimating the term…
A method for obtaining a shape interpolated representation of shapes of one or more clusters in an image of a dataset that has been clustered 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 in the image 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 of each grid point; and adding each grid point for which the maximum density estimate value exceeds a specified threshold to the cluster associated with the maximum density estimate value for the grid point to form a shape interpolated representation of the one or more clusters.
A method executed on a computer for obtaining a shape interpolated representation of shapes of one or more clusters in an image of a dataset that has been clustered, the method comprising:
Dependencies are inferred from the claim text.