Method and Apparatus for Selecting Clusterings to Classify A Predetermined Data Set

Citation:

Gary King and Justin Grimmer. 2013. “Method and Apparatus for Selecting Clusterings to Classify A Predetermined Data Set.” United States of America 8,438,162 (May 7). US Copy at http://j.mp/2ovzAuR
Patent694 KB
Method and Apparatus for Selecting Clusterings to Classify A Predetermined Data Set

Abstract:

A method for selecting clusterings to classify a predetermined data set of numerical data comprises five steps. First, a plurality of known clustering methods are applied, one at a time, to the data set to generate clusterings for each method. Second, a metric space of clusterings is generated using a metric that measures the similarity between two clusterings. Third, the metric space is projected to a lower dimensional representation useful for visualization. Fourth, a “local cluster ensemble” method generates a clustering for each point in the lower dimensional space. Fifth, an animated visualization method uses the output of the local cluster ensemble method to display the lower dimensional space and to allow a user to move around and explore the space of clustering.

Last updated on 03/06/2015