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A Comparison of Classifiers for Solar Energetic Events

Published online by Cambridge University Press:  30 May 2017

Graham Barnes Open the ORCID record for Graham Barnes [Opens in a new window] ,
Nicole Schanche ,
K. D. Leka ,
Ashna Aggarwal  and
Kathy Reeves
Graham Barnes
Affiliation:
NorthWest Research Associates, 3380 Mitchell Ln, Boulder CO 80305, USA email: graham@nwra.com, leka@nwra.com
Nicole Schanche
Affiliation:
University of St Andrews, North Haught, St Andrews, Fife, KY16 9SS, UK email: ns81@st-andrews.ac.uk
K. D. Leka
Affiliation:
NorthWest Research Associates, 3380 Mitchell Ln, Boulder CO 80305, USA email: graham@nwra.com, leka@nwra.com
Ashna Aggarwal
Affiliation:
Department of Earth, Planetary, and Space Science, University of California, Los Angeles CA 90095, USA email: aaggarwal01@ucla.edu
Kathy Reeves
Affiliation:
Harvard Smithsonian Center for Astrophysics, Cambridge MA 02138, USA email: kreeves@cfa.harvard.edu
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Abstract

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We compare the results of using a Random Forest Classifier with the results of using Nonparametric Discriminant Analysis to classify whether a filament channel (in the case of a filament eruption) or an active region (in the case of a flare) is about to produce an event. A large number of descriptors are considered in each case, but it is found that only a small number are needed in order to get most of the improvement in performance over always predicting the majority class. There is little difference in performance between the two classifiers, and neither results in substantial improvements over simply predicting the majority class.

Keywords

methods: statisticalSun: coronal mass ejections (CMEs)Sun: filamentsSun: flares
Type
Contributed Papers
Information
Proceedings of the International Astronomical Union , Volume 12 , Symposium S325: Astroinformatics , October 2016 , pp. 201 - 204
Copyright
Copyright © International Astronomical Union 2017 

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