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ELM Regime Classification by Conformal Prediction on an Information Manifold
2015
IEEE Transactions on Plasma Science
Characterisation and control of plasma instabilities known as edge-localised modes (ELMs) is crucial for the operation of fusion reactors. Recently, machine learning methods have demonstrated good potential in making useful inferences from stochastic fusion data sets. However, traditional classification methods do not offer an inherent estimate of the goodness of their prediction. In this work, a distance-based conformal predictor classifier integrated with a geometricprobabilistic framework is
doi:10.1109/tps.2015.2489689
fatcat:3i6kuaqi3vfzxkftiildmi2ytu