CN113632112A - 增强的集成模型多样性和学习 - Google Patents

增强的集成模型多样性和学习 Download PDF

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CN113632112A
CN113632112A CN202080022167.1A CN202080022167A CN113632112A CN 113632112 A CN113632112 A CN 113632112A CN 202080022167 A CN202080022167 A CN 202080022167A CN 113632112 A CN113632112 A CN 113632112A
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S.萨特
D.S.图拉加
C.阿加瓦尔
V.N.帕武鲁里
张元极
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International Business Machines Corp
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    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N20/00—Machine learning
    • G06N20/20—Ensemble learning
    • 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
    • G06F18/2115—Selection of the most significant subset of features by evaluating different subsets according to an optimisation criterion, e.g. class separability, forward selection or backward elimination
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F18/00—Pattern recognition
    • G06F18/20—Analysing
    • G06F18/23—Clustering techniques
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F18/00—Pattern recognition
    • G06F18/20—Analysing
    • G06F18/23—Clustering techniques
    • G06F18/232—Non-hierarchical techniques
    • G06F18/2321—Non-hierarchical techniques using statistics or function optimisation, e.g. modelling of probability density functions
    • G06F18/23213—Non-hierarchical techniques using statistics or function optimisation, e.g. modelling of probability density functions with fixed number of clusters, e.g. K-means clustering
    • 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
    • G06F18/25—Fusion techniques
    • G06F18/254—Fusion techniques of classification results, e.g. of results related to same input data
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F18/00—Pattern recognition
    • G06F18/20—Analysing
    • G06F18/25—Fusion techniques
    • G06F18/259—Fusion by voting

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  • Engineering & Computer Science (AREA)
  • Theoretical Computer Science (AREA)
  • Data Mining & Analysis (AREA)
  • Physics & Mathematics (AREA)
  • Artificial Intelligence (AREA)
  • General Physics & Mathematics (AREA)
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  • Bioinformatics & Computational Biology (AREA)
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  • Life Sciences & Earth Sciences (AREA)
  • Software Systems (AREA)
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  • Mathematical Physics (AREA)
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  • Management, Administration, Business Operations System, And Electronic Commerce (AREA)
  • Information Retrieval, Db Structures And Fs Structures Therefor (AREA)
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CN202080022167.1A 2019-04-11 2020-03-18 增强的集成模型多样性和学习 Pending CN113632112A (zh)

Applications Claiming Priority (3)

Application Number Priority Date Filing Date Title
US16/381,979 US11593716B2 (en) 2019-04-11 2019-04-11 Enhanced ensemble model diversity and learning
US16/381,979 2019-04-11
PCT/IB2020/052472 WO2020208445A1 (en) 2019-04-11 2020-03-18 Enhanced ensemble model diversity and learning

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US (1) US11593716B2 (https=)
JP (1) JP7335352B2 (https=)
CN (1) CN113632112A (https=)
GB (1) GB2598061A (https=)
WO (1) WO2020208445A1 (https=)

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JP7322918B2 (ja) * 2021-03-29 2023-08-08 横河電機株式会社 プログラム、情報処理装置、及び学習モデルの生成方法
US12141806B2 (en) * 2021-05-30 2024-11-12 Actimize Ltd. Clustering-based data selection for optimization of risk predictive machine learning models
US12488063B2 (en) * 2021-09-01 2025-12-02 Unitedhealth Group Incorporated Generating input processing rules engines using probabilistic clustering techniques
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US12541721B2 (en) * 2022-04-03 2026-02-03 Actimize Ltd. Method for extreme class imbalance within fraud detection
KR20240068162A (ko) * 2022-11-10 2024-05-17 삼성전자주식회사 이미지의 객체를 분류하는 분류 방법 및 이를 수행하는 분류 장치
JP2025049280A (ja) * 2023-09-21 2025-04-03 ソフトバンクグループ株式会社 システム
JP2025056785A (ja) * 2023-09-26 2025-04-08 ソフトバンクグループ株式会社 システム
JP7706730B1 (ja) * 2024-08-16 2025-07-14 ＡＩ ｉｎｓｉｄｅ株式会社 プログラム、方法、自律分散処理システム
WO2026038705A1 (ko) * 2024-08-16 2026-02-19 주식회사 Lg 경영개발원 예측 시스템 및 이의 제어 방법, 그리고 예측 시스템의 학습 방법
KR102831812B1 (ko) * 2024-08-16 2025-07-09 주식회사 Lg 경영개발원 예측 시스템 및 이의 제어 방법, 그리고 예측 시스템의 학습 방법

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CN107688831A (zh) * 2017-09-04 2018-02-13 五邑大学 一种基于聚类下采样的不平衡数据分类方法
CN108985369A (zh) * 2018-07-06 2018-12-11 太原理工大学 一种用于非平衡数据集分类的同分布集成预测方法及系统
CN109086412A (zh) * 2018-08-03 2018-12-25 北京邮电大学 一种基于自适应加权Bagging-GBDT的不平衡数据分类方法
CN109492673A (zh) * 2018-10-19 2019-03-19 南京理工大学 一种基于谱聚类采样的不平衡数据预测方法

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Publication number Priority date Publication date Assignee Title
CN118057319A (zh) * 2022-11-21 2024-05-21 慧与发展有限责任合伙企业 使用模体和形状子的单变量时间序列数据集的无监督分割
CN118057319B (zh) * 2022-11-21 2024-12-24 慧与发展有限责任合伙企业 使用模体和形状子的单变量时间序列数据集的无监督分割

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GB2598061A (en) 2022-02-16
WO2020208445A1 (en) 2020-10-15
US11593716B2 (en) 2023-02-28
GB202115645D0 (en) 2021-12-15
US20200327456A1 (en) 2020-10-15
JP7335352B2 (ja) 2023-08-29
JP2022527366A (ja) 2022-06-01

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Application publication date: 20211109