SWFT

The Space Weather Forecasting Testbed is a machine learning tool that allows a user to combine a variety of observations of solar wind and geomagnetic activity indices to form a forecast model of any of the space weather-relevent parameters.

Inputs include a current time, learning interval, cross-validation interval, intended lead time and the forecast type: data (continuous) or categorical (discrete values based on crossing thresholds).

Time series of targeted index values during learning and validation intervals, scatter plot of model-data comparison and error distribution.