Centroid detection for clustering

A method of categorizing data points is described which, when combined with a clustering algorithm, provides groupings of data points that have an improved confidence interval. The method can be used to find an optimal number of groupings for a dataset, which in turn allows a user to categorize a gr...

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Bibliographic Details
Main Authors CHAKRAVARTHY DIWAKAR, DYKSTRA AARON JAMES, DAI SIYANG
Format Patent
LanguageEnglish
Published 08.03.2016
Subjects
CALCULATING
COMPUTING
COUNTING
ELECTRIC DIGITAL DATA PROCESSING
PHYSICS
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Summary:A method of categorizing data points is described which, when combined with a clustering algorithm, provides groupings of data points that have an improved confidence interval. The method can be used to find an optimal number of groupings for a dataset, which in turn allows a user to categorize a group of data points for processing. In some examples, a dataset containing a number of data points may be accessed. Additionally, in some aspects, groupings of data points within the dataset may be grouped based at least in part on similarities between the data. Further, a number of groupings of data points may be adjusted so that the distance between the data points within one or more groupings of data points may fit within a confidence level.
Bibliography:Application Number: US201313949526