A hybrid supervised/unsupervised machine learning approach to solar flare prediction

2017/06/21 by Federico Benvenuto, Michele Piana, Cristina Campi +1 · 1 citation
Physics and Astronomy · Computer Science · #astro-ph.SR #cs.LG #msc:85-08

paper · pdf · doi:10.3847/1538-4357/aaa23c

arxiv created 2017/06/21 · arxiv updated 2018/02/07

Abstract

We introduce a hybrid approach to solar flare prediction, whereby a supervised regularization method is used to realize feature importance and an unsupervised clustering method is used to realize the binary flare/no-flare decision. The approach is validated against NOAA SWPC data.

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