The flare likelihood and region eruption forecasting (FLARECAST) project: flare forecasting in the big data & machine learning era | Journal of Space Weather and Space Climate

Topical Issue - Space Weather research in the Digital Age and across the full data lifecycle

Open Access

Table 2

FLARECAST unsupervised and supervised machine learning methods (final release).

Unsupervised methods	K-means Fuzzy C-means Possibilistic C-means
Supervised methods	LASSO Hybrid LASSO Elastic net Logit Hybrid Logit Random forests (RFs) Multi-layer perceptron (MLP) Recurrent neural network (RNN) Support vector machine (SVM) Garson’s method Olden’s method

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.