KR102684032B1 - 분류 모델의 정확도 개선 - Google Patents

분류 모델의 정확도 개선 Download PDF

Info

Publication number
KR102684032B1
KR102684032B1 KR1020227022704A KR20227022704A KR102684032B1 KR 102684032 B1 KR102684032 B1 KR 102684032B1 KR 1020227022704 A KR1020227022704 A KR 1020227022704A KR 20227022704 A KR20227022704 A KR 20227022704A KR 102684032 B1 KR102684032 B1 KR 102684032B1
Authority
KR
South Korea
Prior art keywords
hypothesis
hypotheses
classification model
graph
model
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.)
Active
Application number
KR1020227022704A
Other languages
English (en)
Korean (ko)
Other versions
KR20220110264A (ko
Inventor
고넨 라베
엘라드 고센
Original Assignee
오르보테크 엘티디.
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 오르보테크 엘티디. filed Critical 오르보테크 엘티디.
Publication of KR20220110264A publication Critical patent/KR20220110264A/ko
Application granted granted Critical
Publication of KR102684032B1 publication Critical patent/KR102684032B1/ko
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Classifications

    • 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
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F18/00—Pattern recognition
    • G06F18/20—Analysing
    • G06F18/24—Classification techniques
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F18/00—Pattern recognition
    • G06F18/20—Analysing
    • G06F18/29—Graphical models, e.g. Bayesian networks
    • 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
    • G06N3/004—Artificial life, i.e. computing arrangements simulating life
    • G06N3/006—Artificial life, i.e. computing arrangements simulating life based on simulated virtual individual or collective life forms, e.g. social simulations or particle swarm optimisation [PSO]
    • 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
    • G06N3/04—Architecture, e.g. interconnection topology
    • G06N3/0464—Convolutional networks [CNN, ConvNet]
    • 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
    • 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
    • G06N3/0895—Weakly supervised learning, e.g. semi-supervised or self-supervised 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
    • G06N3/09—Supervised 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
    • G06N3/092—Reinforcement 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
    • G06N7/00—Computing arrangements based on specific mathematical models
    • G06N7/01—Probabilistic graphical models, e.g. probabilistic networks
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00—Arrangements for image or video recognition or understanding
    • G06V10/70—Arrangements for image or video recognition or understanding using pattern recognition or machine learning
    • G06V10/764—Arrangements for image or video recognition or understanding using pattern recognition or machine learning using classification, e.g. of video objects
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00—Arrangements for image or video recognition or understanding
    • G06V10/70—Arrangements for image or video recognition or understanding using pattern recognition or machine learning
    • G06V10/77—Processing image or video features in feature spaces; using data integration or data reduction, e.g. principal component analysis [PCA] or independent component analysis [ICA] or self-organising maps [SOM]; Blind source separation
    • G06V10/774—Generating sets of training patterns; Bootstrap methods, e.g. bagging or boosting
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00—Arrangements for image or video recognition or understanding
    • G06V10/70—Arrangements for image or video recognition or understanding using pattern recognition or machine learning
    • G06V10/77—Processing image or video features in feature spaces; using data integration or data reduction, e.g. principal component analysis [PCA] or independent component analysis [ICA] or self-organising maps [SOM]; Blind source separation
    • G06V10/776—Validation; Performance evaluation
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00—Arrangements for image or video recognition or understanding
    • G06V10/70—Arrangements for image or video recognition or understanding using pattern recognition or machine learning
    • G06V10/77—Processing image or video features in feature spaces; using data integration or data reduction, e.g. principal component analysis [PCA] or independent component analysis [ICA] or self-organising maps [SOM]; Blind source separation
    • G06V10/778—Active pattern-learning, e.g. online learning of image or video features
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00—Arrangements for image or video recognition or understanding
    • G06V10/70—Arrangements for image or video recognition or understanding using pattern recognition or machine learning
    • G06V10/77—Processing image or video features in feature spaces; using data integration or data reduction, e.g. principal component analysis [PCA] or independent component analysis [ICA] or self-organising maps [SOM]; Blind source separation
    • G06V10/778—Active pattern-learning, e.g. online learning of image or video features
    • G06V10/7784—Active pattern-learning, e.g. online learning of image or video features based on feedback from supervisors
    • G06V10/7788—Active pattern-learning, e.g. online learning of image or video features based on feedback from supervisors the supervisor being a human, e.g. interactive learning with a human teacher
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00—Arrangements for image or video recognition or understanding
    • G06V10/70—Arrangements for image or video recognition or understanding using pattern recognition or machine learning
    • G06V10/82—Arrangements for image or video recognition or understanding using pattern recognition or machine learning using neural networks
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00—Arrangements for image or video recognition or understanding
    • G06V10/70—Arrangements for image or video recognition or understanding using pattern recognition or machine learning
    • G06V10/84—Arrangements for image or video recognition or understanding using pattern recognition or machine learning using probabilistic graphical models from image or video features, e.g. Markov models or Bayesian networks

Landscapes

  • Engineering & Computer Science (AREA)
  • Theoretical Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • Evolutionary Computation (AREA)
  • General Physics & Mathematics (AREA)
  • Artificial Intelligence (AREA)
  • Software Systems (AREA)
  • Computing Systems (AREA)
  • Data Mining & Analysis (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • General Health & Medical Sciences (AREA)
  • Health & Medical Sciences (AREA)
  • Databases & Information Systems (AREA)
  • General Engineering & Computer Science (AREA)
  • Medical Informatics (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Multimedia (AREA)
  • Mathematical Physics (AREA)
  • Molecular Biology (AREA)
  • Biomedical Technology (AREA)
  • Biophysics (AREA)
  • Computational Linguistics (AREA)
  • Bioinformatics & Cheminformatics (AREA)
  • Bioinformatics & Computational Biology (AREA)
  • Evolutionary Biology (AREA)
  • Probability & Statistics with Applications (AREA)
  • Algebra (AREA)
  • Computational Mathematics (AREA)
  • Mathematical Analysis (AREA)
  • Mathematical Optimization (AREA)
  • Pure & Applied Mathematics (AREA)
  • Image Analysis (AREA)
KR1020227022704A 2019-12-05 2020-11-08 분류 모델의 정확도 개선 Active KR102684032B1 (ko)

Applications Claiming Priority (3)

Application Number Priority Date Filing Date Title
US201962943812P 2019-12-05 2019-12-05
US62/943,812 2019-12-05
PCT/IL2020/051157 WO2021111431A1 (en) 2019-12-05 2020-11-08 Improving accuracy of classification models

Publications (2)

Publication Number Publication Date
KR20220110264A KR20220110264A (ko) 2022-08-05
KR102684032B1 true KR102684032B1 (ko) 2024-07-10

Family

ID=76210950

Family Applications (1)

Application Number Title Priority Date Filing Date
KR1020227022704A Active KR102684032B1 (ko) 2019-12-05 2020-11-08 분류 모델의 정확도 개선

Country Status (6)

Country Link
US (1) US11640559B2 (https=)
JP (1) JP7477608B2 (https=)
KR (1) KR102684032B1 (https=)
CN (1) CN114787831B (https=)
TW (1) TWI834011B (https=)
WO (1) WO2021111431A1 (https=)

Families Citing this family (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US12067571B2 (en) * 2020-03-11 2024-08-20 Synchrony Bank Systems and methods for generating models for classifying imbalanced data
US20220292661A1 (en) * 2021-03-10 2022-09-15 Adlink Technology Inc. Automated inspection system and operating method thereof
US12217277B2 (en) * 2021-06-18 2025-02-04 Blue Boat Data Inc System and method for in-store customer feedback collection and utilization
US11663023B2 (en) * 2021-07-21 2023-05-30 The Travelers Indemnity Company Systems and methods for dynamic artificial intelligence (AI) graphical user interface (GUI) generation
US12586309B2 (en) 2023-02-01 2026-03-24 Vizuro Taiwan Company Ltd. Machine-learning method on vectorized three-dimensional model and learning system thereof
TWI892076B (zh) * 2023-02-02 2025-08-01 維曙智能科技有限公司 向量化立體模型機器學習方法與學習系統
KR102742448B1 (ko) * 2023-12-19 2024-12-18 항공안전기술원 항공안전데이터의 위해요인 자동 분류 시스템 및 방법

Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20120093396A1 (en) 2010-10-13 2012-04-19 Shengyang Dai Digital image analysis utilizing multiple human labels
WO2018130267A1 (en) 2017-01-10 2018-07-19 Huawei Technologies Co., Ltd. Systems and methods for fault tolerance recover during training of a model of a classifier using a distributed system
US10719301B1 (en) 2018-10-26 2020-07-21 Amazon Technologies, Inc. Development environment for machine learning media models

Family Cites Families (10)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US9672474B2 (en) * 2014-06-30 2017-06-06 Amazon Technologies, Inc. Concurrent binning of machine learning data
US11100420B2 (en) * 2014-06-30 2021-08-24 Amazon Technologies, Inc. Input processing for machine learning
EP3161635B1 (en) * 2014-06-30 2023-11-01 Amazon Technologies, Inc. Machine learning service
US9886670B2 (en) * 2014-06-30 2018-02-06 Amazon Technologies, Inc. Feature processing recipes for machine learning
US10713589B1 (en) * 2016-03-03 2020-07-14 Amazon Technologies, Inc. Consistent sort-based record-level shuffling of machine learning data
US10674159B2 (en) * 2017-07-28 2020-06-02 Microsoft Technology Licensing, Llc Effective intra encoding for screen data
CN107391760B (zh) * 2017-08-25 2018-05-25 平安科技（深圳）有限公司 用户兴趣识别方法、装置及计算机可读存储介质
US11494689B2 (en) * 2018-06-05 2022-11-08 Chatterbox Labs Limited Method and device for improved classification
JP7243333B2 (ja) * 2019-03-15 2023-03-22 富士通株式会社 情報処理方法、情報処理プログラム、および情報処理装置
CN110334742B (zh) * 2019-06-10 2021-06-29 浙江大学 一种用于文档分类的基于强化学习的通过添加虚假节点的图对抗样本生成方法

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20120093396A1 (en) 2010-10-13 2012-04-19 Shengyang Dai Digital image analysis utilizing multiple human labels
WO2018130267A1 (en) 2017-01-10 2018-07-19 Huawei Technologies Co., Ltd. Systems and methods for fault tolerance recover during training of a model of a classifier using a distributed system
US20190220758A1 (en) 2017-01-10 2019-07-18 Huawei Technologies Co., Ltd. Systems and methods for fault tolerance recover during training of a model of a classifier using a distributed system
US10719301B1 (en) 2018-10-26 2020-07-21 Amazon Technologies, Inc. Development environment for machine learning media models

Also Published As

Publication number Publication date
TWI834011B (zh) 2024-03-01
CN114787831A (zh) 2022-07-22
CN114787831B (zh) 2024-04-16
KR20220110264A (ko) 2022-08-05
JP2023505201A (ja) 2023-02-08
WO2021111431A1 (en) 2021-06-10
TW202139079A (zh) 2021-10-16
US11640559B2 (en) 2023-05-02
JP7477608B2 (ja) 2024-05-01
US20210174148A1 (en) 2021-06-10

Similar Documents

Publication Publication Date Title
KR102684032B1 (ko) 분류 모델의 정확도 개선
JP7675093B2 (ja) 画像分類のための適応学習
CN111767930A (zh) 物联网时序数据异常检测方法及其相关设备
US11288065B2 (en) Devops driven cognitive cost function for software defect prediction
Tanaka et al. Prediction of software defects using automated machine learning
Dam et al. DeepSoft: A vision for a deep model of software
JP2024041064A (ja) センサ測定値の異常検出
Braiek et al. TFCheck: A tensorflow library for detecting training issues in neural network programs
CN117272311A (zh) 源代码漏洞预测方法及装置
KR102805338B1 (ko) 뉴럴 네트워크 장치 및 그 장치에서의 러닝 방법
Dhavakumar et al. Software defect prediction using graph sample and aggregate-attention network optimized with nomadic people optimizer for enhancing the software reliability
CN119539185A (zh) 氨气传感器的数据优化和预警方法、系统、设备及介质
Matcha et al. Using Deep Learning Classifiers to Identify Candidate Classes for Unit Testing in Object-Oriented Systems.
Tyrovolas et al. A novel framework for enhanced interpretability in fuzzy cognitive maps
Mohana Ramya et al. Software fault prediction using deep neural networks
Kaushal et al. PSO based neural network approaches for prediction of level of severity of faults in nasa’s public domain defect dataset
Syed et al. A Self-Learning Framework for Enhancing Data Quality in Data-Centric AI Systems through Continuous Feedback
Sudharson et al. Software Quality Prediction by CatBoostFeed-Forward Neural Network in Software Engineering
US20190087407A1 (en) Method and system for inferential data mining
US20250355632A1 (en) Teaching algorithmic reasoning to generative models via execution traces
Poornima et al. Software Quality Prediction by CatBoost
Mocke Leveraging Retrieval-Augmented Generation, Prompt Engineering, and Vision Language Models for Surface Defect Classification and Root Cause Analysis in Manufacturing
Siri et al. Software Quality Sustainability Measurement Using Machine Learning Algorithms
CN120476450A (zh) 医学设备故障预测
CN118871920A (zh) 专家最优相关性：用于无监督异常检测的污染因子识别

Legal Events

Date Code Title Description
PA0105 International application

Patent event date: 20220701

Patent event code: PA01051R01D

Comment text: International Patent Application

PG1501 Laying open of application
E902 Notification of reason for refusal
PE0902 Notice of grounds for rejection

Comment text: Notification of reason for refusal

Patent event date: 20231205

Patent event code: PE09021S01D

E701 Decision to grant or registration of patent right
PE0701 Decision of registration

Patent event code: PE07011S01D

Comment text: Decision to Grant Registration

Patent event date: 20240619

GRNT Written decision to grant
PR0701 Registration of establishment

Comment text: Registration of Establishment

Patent event date: 20240708

Patent event code: PR07011E01D

PR1002 Payment of registration fee

Payment date: 20240708

End annual number: 3

Start annual number: 1

PG1601 Publication of registration