ZA202301444B - Generating noisy copies of training data in a method for detecting anomalies - Google Patents

Generating noisy copies of training data in a method for detecting anomalies

Info

Publication number
ZA202301444B
ZA202301444B ZA2023/01444A ZA202301444A ZA202301444B ZA 202301444 B ZA202301444 B ZA 202301444B ZA 2023/01444 A ZA2023/01444 A ZA 2023/01444A ZA 202301444 A ZA202301444 A ZA 202301444A ZA 202301444 B ZA202301444 B ZA 202301444B
Authority
ZA
South Africa
Prior art keywords
noisy
detecting anomalies
training data
copies
generating
Prior art date
Application number
ZA2023/01444A
Inventor
Roman Moscoviz
Original Assignee
Suez Int
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Suez Int filed Critical Suez Int
Publication of ZA202301444B publication Critical patent/ZA202301444B/en

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Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N20/00—Machine learning
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computing arrangements based on biological models
    • G06N3/02—Neural networks
    • G06N3/04—Architecture, e.g. interconnection topology
    • G06N3/045—Combinations of networks
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computing arrangements based on biological models
    • G06N3/02—Neural networks
    • G06N3/08—Learning methods
    • G06N3/088—Non-supervised learning, e.g. competitive learning
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N5/00—Computing arrangements using knowledge-based models
    • G06N5/01—Dynamic search techniques; Heuristics; Dynamic trees; Branch-and-bound

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  • Engineering & Computer Science (AREA)
  • Theoretical Computer Science (AREA)
  • Software Systems (AREA)
  • Evolutionary Computation (AREA)
  • Data Mining & Analysis (AREA)
  • Medical Informatics (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Physics & Mathematics (AREA)
  • Computing Systems (AREA)
  • General Engineering & Computer Science (AREA)
  • General Physics & Mathematics (AREA)
  • Mathematical Physics (AREA)
  • Artificial Intelligence (AREA)
  • Measurement Of Mechanical Vibrations Or Ultrasonic Waves (AREA)
  • Image Analysis (AREA)
  • Testing And Monitoring For Control Systems (AREA)

Abstract

Computer-implemented method (1) for detecting anomalies in a dataset, implementing an unsupervised machine learning module, comprising a step of generating (10-10'') a plurality of noisy copies of all or some of the data of the training dataset, each noisy copy being obtained based on at least one noise generation parameter, for each noisy copy, a step of training (12-12'') said machine learning module based on said associated noisy training dataset, and a step of determining (14, 14') the noisy training dataset exhibiting a maximum detection performance.
ZA2023/01444A 2020-07-16 2023-02-03 Generating noisy copies of training data in a method for detecting anomalies ZA202301444B (en)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
FR2007444A FR3112634B1 (en) 2020-07-16 2020-07-16 Anomaly detection process
PCT/FR2021/051321 WO2022013503A1 (en) 2020-07-16 2021-07-15 Generating noisy copies of training data in a method for detecting anomalies

Publications (1)

Publication Number Publication Date
ZA202301444B true ZA202301444B (en) 2023-10-25

Family

ID=72885727

Family Applications (1)

Application Number Title Priority Date Filing Date
ZA2023/01444A ZA202301444B (en) 2020-07-16 2023-02-03 Generating noisy copies of training data in a method for detecting anomalies

Country Status (4)

Country Link
EP (1) EP4182859A1 (en)
FR (1) FR3112634B1 (en)
WO (1) WO2022013503A1 (en)
ZA (1) ZA202301444B (en)

Family Cites Families (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP6782679B2 (en) * 2016-12-06 2020-11-11 パナソニック インテレクチュアル プロパティ コーポレーション オブ アメリカＰａｎａｓｏｎｉｃ Ｉｎｔｅｌｌｅｃｔｕａｌ Ｐｒｏｐｅｒｔｙ Ｃｏｒｐｏｒａｔｉｏｎ ｏｆ Ａｍｅｒｉｃａ Information processing equipment, information processing methods and programs

Also Published As

Publication number Publication date
FR3112634A1 (en) 2022-01-21
WO2022013503A1 (en) 2022-01-20
FR3112634B1 (en) 2023-04-28
EP4182859A1 (en) 2023-05-24

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