Method for data classification by kernel density shape interpolation of clusters
First Claim
1. 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:
- 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.
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Abstract
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.
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5 Claims
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1. 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:
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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. - View Dependent Claims (2, 3, 4, 5)
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Specification