Flare forecasting and feature ranking using SDO/HMI data
arXiv:1812.07258 · doi:10.1393/ncc/i2019-19030-1
Abstract
We describe here the application of a machine learning method for flare forecasting using vectors of properties extracted from images provided by the Helioseismic and Magnetic Imager in the Solar Dynamics Observatory (SDO/HMI). We also discuss how the method can be used to quantitatively assess the impact of such properties on the prediction process.
submitted to 'Nuovo Cimento' as proceeding of SOHE3