On robust risk-based active-learning algorithms for enhanced decision support. (arXiv:2201.02555v1 [cs.LG])

Classification models are a fundamental component of physical-asset
management technologies such as structural health monitoring (SHM) systems and
digital twins. Previous work introduced \textit{risk-based active learning}, an
online approach for the development of statistical classifiers that takes into
account the decision-support context in which they are applied. Decision-making
is considered by preferentially querying data labels according to
\textit{expected value of perfect information} (EVPI). Although several
benefits are gained by adopting a risk-based active learning approach,
including improved decision-making performance, the …

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