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ORIGINAL RESEARCH article

Front. Astron. Space Sci.
Sec. Space Physics
Volume 11 - 2024 | doi: 10.3389/fspas.2024.1509061

Feature Importance Analysis of Solar Flares and Prediction Research with Ensemble Machine Learning Models

Provisionally accepted
Yun Yang Yun Yang *
  • School of Mathematical Sciences, Nanjing Normal University, Nanjing, China

The final, formatted version of the article will be published soon.

    Solar flares, as intense solar eruptive events, have a profound impact on space weather, potentially disrupting human activities like spaceflight and communication. Hence, identify the key factors that influence the occurrence of solar flares and accurate forecast holds significant research importance. Considering the imbalance of the flare data set, three ensemble learning models (Balanced Random Forest(BRF), RUSBoost(RBC), and NGBoost(NGB)) were utilized, which have gained popularity in statistical machine learning theory in recent years, combined with imbalanced data sampling techniques, to classify and predict the labels representing flare eruptions in the test set. In this study, these models were used to classify and predict flares with a magnitude ≥ Cand M-class, respectively. After obtaining the feature importance scores of each model, a comprehensive feature importance ranking was derived based on the ranking. The

    Keywords: Solar physics, Solar Activity, solar flares, machine learning, feature selection

    Received: 10 Oct 2024; Accepted: 04 Dec 2024.

    Copyright: © 2024 Yang. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence: Yun Yang, School of Mathematical Sciences, Nanjing Normal University, Nanjing, China

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