Improving decision-making via risk-based active learning: Probabilistic discriminative classifiers. (arXiv:2206.11616v1 [cs.LG])

Gaining the ability to make informed decisions on operation and maintenance
of structures provides motivation for the implementation of structural health
monitoring (SHM) systems. However, descriptive labels for measured data
corresponding to health-states of the monitored system are often unavailable.
This issue limits the applicability of fully-supervised machine learning
paradigms for the development of statistical classifiers to be used in
decision-support in SHM systems. One approach to dealing with this problem is
risk-based active learning. In such an approach, data-label …

active learning arxiv classifiers decision learning lg making risk