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Title:
MULTI-LAYERED MACHINE LEARNING SYSTEM TO SUPPORT ENSEMBLE LEARNING
Document Type and Number:
WIPO Patent Application WO/2020/027454
Kind Code:
A1
Abstract:
A method includes providing input data to a plurality of base models to generate a plurality of intermediate outputs. The base models are non-linear in that different base models are specialized differently such that the different base models are complementary to one another. Each of the base models is generated using a different base classification algorithm in a multi-layered machine learning system. The method also includes processing the intermediate outputs using a fusion model to generate a final output associated with the input data. The fusion model is generated using a meta classification algorithm in the multi-layered machine learning system. The method may also include training the classification algorithms, where training data used by each of at least one of the base classification algorithms is selected based on an uncertainty associated with at least one other of the base classification algorithms.

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Inventors:
MOAZZAMI MOHAMMAD M (US)
YADAV ANIL (US)
Application Number:
PCT/KR2019/008353
Publication Date:
February 06, 2020
Filing Date:
July 08, 2019
Export Citation:
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Assignee:
SAMSUNG ELECTRONICS CO LTD (KR)
International Classes:
G06N3/08; G06N3/04; G06N20/00
Domestic Patent References:
WO2017059022A12017-04-06
Foreign References:
US20140279741A12014-09-18
US20170140297A12017-05-18
US20160217387A12016-07-28
Other References:
PIERO P. BONISSONE: "Lazy Meta-Learning: Creating Customized Model Ensembles on Demand", IEEE WORLD CONGRESS ON COMPUTATIONAL INTELLIGENCE: ADVANCES IN COMPUTATIONAL INTELLIGENCE, 15 June 2012 (2012-06-15), pages 1 - 23, XP047388238, DOI: 10.1007/978-3-642-30687-7_1
Attorney, Agent or Firm:
Y.P.LEE, MOCK & PARTNERS (KR)
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