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:
Nov. 08, 2016

Filed:

May. 22, 2015
Applicant:

Datarobot, Inc., Boston, MA (US);

Inventors:

Jeremy Achin, Boston, MA (US);

Thomas DeGodoy, Melrose, MA (US);

Timothy Owen, Watertown, MA (US);

Xavier Conort, Singapore, SG;

Assignee:

DataRobot, Inc., Boston, MA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06F 17/00 (2006.01); G06N 5/02 (2006.01); G06N 5/04 (2006.01); G06F 9/50 (2006.01); G06Q 10/04 (2012.01); G06Q 10/06 (2012.01);
U.S. Cl.
CPC ...
G06N 5/04 (2013.01); G06F 9/5011 (2013.01); G06N 5/02 (2013.01); G06Q 10/04 (2013.01); G06Q 10/06 (2013.01);
Abstract

Systems and techniques for predictive data analytics are described. In a method for selecting a predictive model for a prediction problem, the suitabilities of predictive modeling procedures for the prediction problem may be determined based on characteristics of the prediction problem and/or on attributes of the respective modeling procedures. A subset of the predictive modeling procedures may be selected based on the determined suitabilities of the selected modeling procedures for the prediction problem. A resource allocation schedule allocating computational resources for execution of the selected modeling procedures may be generated, based on the determined suitabilities of the selected modeling procedures for the prediction problem. Results of the execution of the selected modeling procedures in accordance with the resource allocation schedule may be obtained. A predictive model for the prediction problem may be selected based on those results.


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