Random forests (RF) and RReliefF algorithms are first employed to rank the candidate feature set. 
Random forests
Random forests (RF) and RReliefF algorithms are first employed to rank the candidate feature set.  Our results suggest that RF and RReliefF can find the most informative features and can be successfully used to customize the input of glucose models.
RReliefF
Predictions are performed using support vector regression or Gaussian processes. 
Support vector regression
Predictions are performed using support vector regression or Gaussian processes. 
Gaussian processes