KR20230054701A - 하이브리드 기계 학습 - Google Patents

하이브리드 기계 학습 Download PDF

Info

Publication number
KR20230054701A
KR20230054701A KR1020237009608A KR20237009608A KR20230054701A KR 20230054701 A KR20230054701 A KR 20230054701A KR 1020237009608 A KR1020237009608 A KR 1020237009608A KR 20237009608 A KR20237009608 A KR 20237009608A KR 20230054701 A KR20230054701 A KR 20230054701A
Authority
KR
South Korea
Prior art keywords
machine learning
model
pipeline
learning process
data type
Prior art date
Legal status (The legal status 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 status listed.)
Pending
Application number
KR1020237009608A
Other languages
English (en)
Korean (ko)
Inventor
딜런 블랜차드
타일러 헤이늘
롤랜드 맨프레드 호흐무트
Original Assignee
알테릭스 인코포레이티드
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 알테릭스 인코포레이티드 filed Critical 알테릭스 인코포레이티드
Publication of KR20230054701A publication Critical patent/KR20230054701A/ko
Pending legal-status Critical Current

Links

Images

Classifications

    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N5/00—Computing arrangements using knowledge-based models
    • G06N5/04—Inference or reasoning models
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/90—Details of database functions independent of the retrieved data types
    • G06F16/903—Querying
    • G06F16/9032—Query formulation
    • G06F16/90324—Query formulation using system suggestions
    • G06F16/90328—Query formulation using system suggestions using search space presentation or visualization, e.g. category or range presentation and selection
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F18/00—Pattern recognition
    • G06F18/20—Analysing
    • G06F18/21—Design or setup of recognition systems or techniques; Extraction of features in feature space; Blind source separation
    • G06F18/211—Selection of the most significant subset of features
    • G06F18/2113—Selection of the most significant subset of features by ranking or filtering the set of features, e.g. using a measure of variance or of feature cross-correlation
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F18/00—Pattern recognition
    • G06F18/20—Analysing
    • G06F18/21—Design or setup of recognition systems or techniques; Extraction of features in feature space; Blind source separation
    • G06F18/214—Generating training patterns; Bootstrap methods, e.g. bagging or boosting
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F18/00—Pattern recognition
    • G06F18/20—Analysing
    • G06F18/21—Design or setup of recognition systems or techniques; Extraction of features in feature space; Blind source separation
    • G06F18/217—Validation; Performance evaluation; Active pattern learning techniques
    • G06F18/2178—Validation; Performance evaluation; Active pattern learning techniques based on feedback of a supervisor
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F18/00—Pattern recognition
    • G06F18/20—Analysing
    • G06F18/22—Matching criteria, e.g. proximity measures
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N20/00—Machine learning
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; 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
    • G06N3/096—Transfer learning
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; 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
    • G06N3/0985—Hyperparameter optimisation; Meta-learning; Learning-to-learn
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computing arrangements based on biological models
    • G06N3/02—Neural networks
    • G06N3/10—Interfaces, programming languages or software development kits, e.g. for simulating neural networks
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N5/00—Computing arrangements using knowledge-based models
    • G06N5/04—Inference or reasoning models
    • G06N5/045—Explanation of inference; Explainable artificial intelligence [XAI]; Interpretable artificial intelligence
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/90—Details of database functions independent of the retrieved data types
    • G06F16/903—Querying
    • G06F16/9035—Filtering based on additional data, e.g. user or group profiles

Landscapes

  • Engineering & Computer Science (AREA)
  • Theoretical Computer Science (AREA)
  • Data Mining & Analysis (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • General Engineering & Computer Science (AREA)
  • Artificial Intelligence (AREA)
  • Evolutionary Computation (AREA)
  • Software Systems (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Mathematical Physics (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Computing Systems (AREA)
  • Computational Linguistics (AREA)
  • Bioinformatics & Cheminformatics (AREA)
  • Evolutionary Biology (AREA)
  • Bioinformatics & Computational Biology (AREA)
  • Databases & Information Systems (AREA)
  • Biophysics (AREA)
  • Molecular Biology (AREA)
  • General Health & Medical Sciences (AREA)
  • Biomedical Technology (AREA)
  • Health & Medical Sciences (AREA)
  • Medical Informatics (AREA)
  • Management, Administration, Business Operations System, And Electronic Commerce (AREA)
  • Stored Programmes (AREA)
  • Image Analysis (AREA)
  • Control Of Eletrric Generators (AREA)
  • Steroid Compounds (AREA)
  • Organic Low-Molecular-Weight Compounds And Preparation Thereof (AREA)
  • User Interface Of Digital Computer (AREA)
  • Elevator Control (AREA)
  • Feedback Control In General (AREA)
KR1020237009608A 2020-08-25 2021-08-24 하이브리드 기계 학습 Pending KR20230054701A (ko)

Applications Claiming Priority (3)

Application Number Priority Date Filing Date Title
US17/002,717 US12190251B2 (en) 2020-08-25 2020-08-25 Hybrid machine learning
US17/002,717 2020-08-25
PCT/US2021/047334 WO2022046759A1 (en) 2020-08-25 2021-08-24 Hybrid machine learning

Publications (1)

Publication Number Publication Date
KR20230054701A true KR20230054701A (ko) 2023-04-25

Family

ID=80355680

Family Applications (1)

Application Number Title Priority Date Filing Date
KR1020237009608A Pending KR20230054701A (ko) 2020-08-25 2021-08-24 하이브리드 기계 학습

Country Status (8)

Country Link
US (2) US12190251B2 (https=)
EP (1) EP4205043A4 (https=)
JP (1) JP7806027B2 (https=)
KR (1) KR20230054701A (https=)
CN (1) CN115989509A (https=)
AU (1) AU2021332209B2 (https=)
CA (1) CA3189593A1 (https=)
WO (1) WO2022046759A1 (https=)

Families Citing this family (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20210360017A1 (en) * 2020-05-14 2021-11-18 Cynomi Ltd System and method of dynamic cyber risk assessment
EP3982302A1 (en) * 2020-10-12 2022-04-13 Robert Bosch GmbH Device for and method of automating machine learning
US20220300755A1 (en) * 2021-03-16 2022-09-22 Visa International Service Association Method, System, and Computer Program Product for Predicting Future States Based on Time Series Data Using Feature Engineering and/or Hybrid Machine Learning Models
US12499370B2 (en) * 2021-06-09 2025-12-16 Tata Consultancy Services Limited Systems and methods for determining explainability of machine predicted decisions
US20230289650A1 (en) * 2022-03-09 2023-09-14 International Business Machines Corporation Continuous machine learning system for containerized environment with limited resources
WO2024026393A1 (en) * 2022-07-27 2024-02-01 Indr, Inc. Methods and apparatus for ensemble machine learning models and natural language processing for predicting persona based on input patterns

Family Cites Families (13)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
AU4019901A (en) 1999-09-21 2001-04-24 Andrew E. Borthwick A probabilistic record linkage model derived from training data
US9454767B2 (en) 2013-03-13 2016-09-27 Salesforce.Com, Inc. Systems, methods, and apparatuses for implementing a related command with a predictive query interface
US10452992B2 (en) 2014-06-30 2019-10-22 Amazon Technologies, Inc. Interactive interfaces for machine learning model evaluations
WO2016130858A1 (en) * 2015-02-11 2016-08-18 Skytree, Inc. User interface for unified data science platform including management of models, experiments, data sets, projects, actions, reports and features
US20170308800A1 (en) 2016-04-26 2017-10-26 Smokescreen Intelligence, LLC Interchangeable Artificial Intelligence Perception Systems and Methods
US20180268258A1 (en) * 2017-03-14 2018-09-20 TUPL, Inc. Automated decision making using staged machine learning
JP6840627B2 (ja) * 2017-06-15 2021-03-10 株式会社日立製作所 ハイパーパラメータの評価方法、計算機及びプログラム
CN108830383B (zh) * 2018-05-30 2021-06-08 第四范式（北京）技术有限公司 用于展示机器学习建模过程的方法及系统
US11275485B2 (en) 2018-06-15 2022-03-15 Sap Se Data processing pipeline engine
US10747506B2 (en) * 2018-06-15 2020-08-18 Sap Se Customizing operator nodes for graphical representations of data processing pipelines
CN108898229B (zh) * 2018-06-26 2021-12-14 第四范式（北京）技术有限公司 用于构建机器学习建模过程的方法及系统
CN113168421A (zh) * 2018-12-13 2021-07-23 株式会社半导体能源研究所 内容的分类方法及分类模型的生成方法
US11727314B2 (en) * 2019-09-30 2023-08-15 Amazon Technologies, Inc. Automated machine learning pipeline exploration and deployment

Also Published As

Publication number Publication date
US20250094841A1 (en) 2025-03-20
US20220067541A1 (en) 2022-03-03
JP7806027B2 (ja) 2026-01-26
JP2023539240A (ja) 2023-09-13
AU2021332209B2 (en) 2024-07-25
AU2021332209A1 (en) 2023-03-09
EP4205043A1 (en) 2023-07-05
CN115989509A (zh) 2023-04-18
US12190251B2 (en) 2025-01-07
EP4205043A4 (en) 2024-11-13
CA3189593A1 (en) 2022-03-03
WO2022046759A1 (en) 2022-03-03

Similar Documents

Publication Publication Date Title
US20250094841A1 (en) Hybrid Machine Learning
AU2021343372B2 (en) Computer-based systems, computing components and computing objects configured to implement dynamic outlier bias reduction in machine learning models
AU2022264302B2 (en) Industry specific machine learning applications
US11256991B2 (en) Method of and server for converting a categorical feature value into a numeric representation thereof
EP3355248B1 (en) Security classification by machine learning
AU2021353828B2 (en) System and method of operationalizing automated feature engineering
US20250322259A1 (en) System And Method For Dynamic Hyperparameter Optimization For Large Language Models Using (Few-Shot) Reinforcement Learning
AU2021412848B2 (en) Integrated feature engineering
US20260064550A1 (en) AI-Assisted Project Proposal Generation Triggered By Changes In Prompt-Referenced Datasets

Legal Events

Date Code Title Description
PA0105 International application

St.27 status event code: A-0-1-A10-A15-nap-PA0105

PA0201 Request for examination

St.27 status event code: A-1-2-D10-D11-exm-PA0201

PG1501 Laying open of application

St.27 status event code: A-1-1-Q10-Q12-nap-PG1501

D21 Rejection of application intended

Free format text: ST27 STATUS EVENT CODE: A-1-2-D10-D21-EXM-PE0902 (AS PROVIDED BY THE NATIONAL OFFICE)

PE0902 Notice of grounds for rejection

St.27 status event code: A-1-2-D10-D21-exm-PE0902

P11 Amendment of application requested

Free format text: ST27 STATUS EVENT CODE: A-2-2-P10-P11-NAP-X000 (AS PROVIDED BY THE NATIONAL OFFICE)

P11-X000 Amendment of application requested

St.27 status event code: A-2-2-P10-P11-nap-X000