The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Feb. 21, 2017

Filed:

Dec. 05, 2012
Applicant:

Microsoft Corporation, Redmond, WA (US);

Inventors:

Sandipan Ganguly, Bothell, WA (US);

Lu Xia, Shanghai, CN;

Weiwei Wu, Bellevue, WA (US);

Shoou-Jiun Wang, Redmond, WA (US);

Justin Hobart, Kirkland, WA (US);

Assignee:
Attorneys:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
G06F 15/18 (2006.01); G06Q 10/06 (2012.01); G06N 99/00 (2010.01); G06K 9/62 (2006.01); G06N 5/02 (2006.01); G06N 7/00 (2006.01);
U.S. Cl.
CPC ...
G06Q 10/0637 (2013.01); G06Q 10/067 (2013.01); G06Q 10/06375 (2013.01); G06K 9/6256 (2013.01); G06K 9/6269 (2013.01); G06N 5/025 (2013.01); G06N 7/005 (2013.01); G06N 99/005 (2013.01);
Abstract

Self-learning and adaptive modeling is employed with respect to predictive analytics. A hierarchical model structure can be employed comprising a set of predictive models automatically built from accumulated data and distributed across multiple levels. For a given input type, a set of candidate models can be identified across varying levels of granularity, and a best model selected based on a comparison of performance metrics of the models. The best model can then be activated for use in making predictions. Of course, the best model can change based on most recent training performance results, since as more data becomes available more specific models can be developed.


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