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:
Apr. 06, 2021

Filed:

Mar. 03, 2016
Applicant:

International Business Machines Corporation, Armonk, NY (US);

Inventors:

Girish B. Chafle, New Delhi, IN;

Peng Fei Chen, Beijing, CN;

Fan Jing Meng, Beijing, CN;

Hai Shan Wu, Beijing, CN;

Jing Min Xu, Beijing, CN;

Lin Yang, Beijing, CN;

Attorneys:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
G06N 20/00 (2019.01); G06F 11/263 (2006.01); G06F 11/34 (2006.01); G06N 20/10 (2019.01); G06F 11/30 (2006.01);
U.S. Cl.
CPC ...
G06F 11/263 (2013.01); G06F 11/3452 (2013.01); G06N 20/00 (2019.01); G06N 20/10 (2019.01); G06F 11/3006 (2013.01); G06F 11/3414 (2013.01);
Abstract

Embodiments are directed to a computer implemented method for generating a drift detector. The method includes generating, using a processor system, drift cases based at least in part on known drift set data of a computer system. The method further includes injecting, using the processor system, the drift cases into the computer system to generate a first data set. The method further includes applying, using the processor system, cleaning rules to the first data set to reduce a size of the first data set and generate a cleaned data set. The method further includes extracting one or more features of the cleaned data set. The method further includes normalizing the extracted one or more features of the cleaned data set. The method further includes training a machine learning system using the extracted and normalized one or more features of the cleaned data, wherein an output of the machine learning system comprises the drift detector.


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