METHOD AND APPARATUS FOR CONCEPT DRIFT MITIGATION

Method and apparatus for adapting a distribution model of a machine learning fabric. The distribution model is for mitigating the effect of concept drift, and is configured to provide an output as input to a functional model of the machine learning fabric. The functional model is for performing a ma...

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Bibliographic Details
Main Authors GONZALEZ HUESCA, Juan Manuel, LANCIA, Carlo, KOULIERAKIS, Eleftherios, YPMA, Alexander
Format Patent
LanguageEnglish
Published 10.08.2023
Subjects
APPARATUS SPECIALLY ADAPTED THEREFOR
CALCULATING
CINEMATOGRAPHY
COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
COMPUTING
COUNTING
ELECTROGRAPHY
HOLOGRAPHY
MATERIALS THEREFOR
ORIGINALS THEREFOR
PHOTOGRAPHY
PHOTOMECHANICAL PRODUCTION OF TEXTURED OR PATTERNED SURFACES,e.g. FOR PRINTING, FOR PROCESSING OF SEMICONDUCTORDEVICES
PHYSICS
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Summary:Method and apparatus for adapting a distribution model of a machine learning fabric. The distribution model is for mitigating the effect of concept drift, and is configured to provide an output as input to a functional model of the machine learning fabric. The functional model is for performing a machine learning task. The method may include obtaining a first data point, and providing the first data point as input to one or more distribution monitoring components of the distribution model. The one or more distribution monitoring components have been trained on a plurality of further data points. A metric representing a correspondence between the first data point and the plurality of further data points is determined, by at least one of the one or more distribution monitoring components. Based on the error metric, the output of the distribution model is adapted.
Bibliography:Application Number: US202118015162