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:
May. 30, 2023

Filed:

Jan. 31, 2020
Applicant:

Emc Ip Holding Company Llc, Hopkinton, MA (US);

Inventors:

Rahul Vishwakarma, Bangalore, IN;

Shelesh Chopra, Bangalore, IN;

Gopal Singh, Lucknow, IN;

Sujan Kumar Shetty, Karnataka, IN;

Assignee:

EMC IP Holding Company LLC, Hopkinton, MA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06F 17/17 (2006.01); G16Y 40/35 (2020.01); G06N 20/00 (2019.01); H04W 84/18 (2009.01); G06F 17/11 (2006.01); G16Y 40/20 (2020.01); G06F 17/16 (2006.01); G06F 17/18 (2006.01);
U.S. Cl.
CPC ...
G06F 17/17 (2013.01); G06F 17/11 (2013.01); G06F 17/16 (2013.01); G06F 17/18 (2013.01); G06N 20/00 (2019.01); G16Y 40/20 (2020.01); G16Y 40/35 (2020.01); H04W 84/18 (2013.01);
Abstract

Methods, apparatus, and processor-readable storage media for analyzing time series data for sets of devices using machine learning techniques are provided herein. An example computer-implemented method includes processing time series data from multiple devices; generating at least one data forecast by applying, in response to a request from at least one user, one or more machine learning techniques to at least a portion of the processed time series data; computing one or more qualifying values attributable to the at least one generated data forecast by providing the at least one generated data forecast and the at least a portion of the processed time series data to a conformal prediction framework; and performing one or more automated actions based at least in part on the at least one generated data forecast and the one or more computed qualifying values.


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