METHOD FOR FAIRNESS-AWARE DATA VALUATION PROCESSING FOR SUPERVISED LEARNING

The present document discloses a method for machine-learning fairness-aware data valuation processing for supervised learning, from a training dataset comprising a plurality of data records each containing data for a training instance for said supervised learning, wherein the data for each training...

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Main Authors DOS SANTOS SALEIRO, PEDRO, SANTOS RODRIGUES BIZARRO, PEDRO GUSTAVO, PEREIRA ROSA CORREIA POMBAL, JOSÉ MARIA
Format Patent
LanguageEnglish
Published 23.05.2024
Subjects
CALCULATING
COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
COMPUTING
COUNTING
PHYSICS
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Summary:The present document discloses a method for machine-learning fairness-aware data valuation processing for supervised learning, from a training dataset comprising a plurality of data records each containing data for a training instance for said supervised learning, wherein the data for each training instance comprises one or more target variables, one or more input variables and one or more protected-attribute variables, wherein fairness is defined as minimizing a data bias present in the training set in respect of the one or more protected variables.
Bibliography:Application Number: US202318507568