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:
Sep. 03, 2024

Filed:

Dec. 14, 2020
Applicant:

Microsoft Technology Licensing, Llc, Redmond, WA (US);

Inventors:

Yuting Jia, Redmond, WA (US);

Jayaram N. M. Nanduri, Issaquah, WA (US);

Kiyoung Yang, Sammamish, WA (US);

Yini Zhang, Bellevue, WA (US);

Assignee:
Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06N 20/00 (2019.01); G06F 17/18 (2006.01); G06F 18/2135 (2023.01); G06F 18/2433 (2023.01); G06Q 10/0633 (2023.01);
U.S. Cl.
CPC ...
G06F 18/2433 (2023.01); G06F 17/18 (2013.01); G06F 18/2135 (2023.01); G06Q 10/0633 (2013.01);
Abstract

Different automatic tasks are facilitated via outlier detection in datasets using a Weighted Histogram-based Outlier Scoring (W-HBOS). An initial set of features is extracted from a processed dataset. The initial set of features is further filtered by applying robust statistics for size reduction. A second round of automatic feature selection is implemented based on maximum-entropy estimation so that a selected set of features that can give maximum possible information from different dimensions towards detecting anomalies are selected. The selected set of features are transformed to generate principal components that are provided to the W-HBOS-based model for outlier detection. A subset of outliers in one of the directions can be selected and reason codes are identified using back transformation for the execution of a desired automatic task.


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