AU2021332209B2 - Hybrid machine learning - Google Patents

Hybrid machine learning Download PDF

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Publication number
AU2021332209B2
AU2021332209B2 AU2021332209A AU2021332209A AU2021332209B2 AU 2021332209 B2 AU2021332209 B2 AU 2021332209B2 AU 2021332209 A AU2021332209 A AU 2021332209A AU 2021332209 A AU2021332209 A AU 2021332209A AU 2021332209 B2 AU2021332209 B2 AU 2021332209B2
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machine learning
model
pipeline
feature
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AU2021332209A
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AU2021332209A1 (en
Inventor
Dylan BLANCHARD
Tyler HEINL
Roland Manfred Hochmuth
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Alteryx Inc
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Alteryx Inc
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    • 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

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  • 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)
AU2021332209A 2020-08-25 2021-08-24 Hybrid machine learning Active AU2021332209B2 (en)

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 (2)

Publication Number Publication Date
AU2021332209A1 AU2021332209A1 (en) 2023-03-09
AU2021332209B2 true AU2021332209B2 (en) 2024-07-25

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AU2021332209A Active AU2021332209B2 (en) 2020-08-25 2021-08-24 Hybrid machine learning

Country Status (8)

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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=)

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* Cited by examiner, † Cited by third party
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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

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* Cited by examiner, † Cited by third party
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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
KR20230054701A (ko) 2023-04-25
US20250094841A1 (en) 2025-03-20
US20220067541A1 (en) 2022-03-03
JP7806027B2 (ja) 2026-01-26
JP2023539240A (ja) 2023-09-13
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

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