Hybrid clustering for data analytics
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United States of America Patent
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Nov 8, 2016
Grant Date -
May 22, 2014
app pub date -
Jul 1, 2013
filing date -
Nov 19, 2012
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Abstract
The invention includes methods and systems for analyzing data to determine trends in the data and to identify outliers. The methods and systems include a learning algorithm whereby a data space is co-populated with artificial, evenly distributed data, and then the data space is carved into smaller portions whereupon the number of real and artificial data points are compared. Through an iterative process, clusters having less than evenly distributed real data are discarded. Additionally, a final quality control measurement is used to merge clusters that are too similar to be meaningful. The invention is widely applicable to data analytics, generally, including financial transactions, retail sales, elections, and sports.
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