Machine Learning in Heliophysics and Space Weather Forecasting: A White Paper of Findings and Recommendations.
Gelu NitaManolis K. GeorgoulisIrina KitiashviliViacheslav SadykovEnrico CamporealeAlexander KosovichevHaimin WangVincent OriaJason T. L. WangRafal A. AngrykBerkay AydinAzim AhmadzadehXiaoli BaiTimothy BastianSoukaina Filali BoubrahimiBin ChenAlisdair DaveySheldon FereiraGregory FleishmanDale GaryAndrew GerrardGregory HellbourgKatherine HerbertJack IrelandEgor IllarionovNatsuha KurodaQin LiChang LiuYuexin LiuHyomin KimDustin KemptonRuizhe MaPetrus C. MartensRyan M. McGranaghanEdward SemonesJohn StefanAndrey StejkoYaireska Collado-VegaMeiqi WangYan XuSijie YuPublished in: CoRR (2020)
Keyphrases
- weather forecasting
- machine learning
- learning algorithm
- data mining
- case study
- higher dimensional
- empirical evidence
- decision trees
- recommender systems
- vector space
- knowledge acquisition
- text classification
- low dimensional
- artificial intelligence
- search space
- database
- support vector machine
- natural language processing
- e learning
- feature selection
- computer vision
- learning systems
- space time
- machine learning methods
- learning tasks
- real world
- literature review
- neural network
- data sets