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:
Oct. 05, 2021

Filed:

Oct. 23, 2018
Applicant:

Oracle International Corporation, Redwood Shores, CA (US);

Inventors:

Dustin Garvey, Exeter, NH (US);

Sampanna Shahaji Salunke, Dublin, CA (US);

Uri Shaft, Fremont, CA (US);

Sumathi Gopalakrishnan, Fremont, CA (US);

Assignee:

Oracle International Corporation, Redwood Shores, CA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06F 11/34 (2006.01); G06F 17/18 (2006.01); G06F 16/28 (2019.01); G06K 9/62 (2006.01); G06N 20/00 (2019.01); G06N 7/00 (2006.01);
U.S. Cl.
CPC ...
G06F 11/3452 (2013.01); G06F 11/3419 (2013.01); G06F 16/285 (2019.01); G06F 17/18 (2013.01); G06K 9/6262 (2013.01); G06K 9/6284 (2013.01); G06N 7/005 (2013.01); G06N 20/00 (2019.01); G06F 2201/81 (2013.01); G06F 2201/835 (2013.01);
Abstract

Techniques for training and evaluating seasonal forecasting models are disclosed. In some embodiments, a network service generates, in memory, a set of data structures that separate sample values by season type and season space. The set of data structures may include a first set of clusters corresponding to different season types in the first season space and a second set of clusters corresponding to different season types in the second season space. The network service merges two or more clusters the first set and/or second set of clusters. Clusters from the first set are not merged with clusters from the second set. After merging the clusters, the network service determines a trend pattern for each of the remaining clusters in the first and second set of clusters. The network service then generates a forecast for a metric of a computing resource based on the trend patterns for each remaining cluster.


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