Feature processor for EQRN

Usage

process_features(
  X,
  intermediate_q_feature,
  intermediate_quantiles = NULL,
  X_scaling = NULL,
  scale_features = TRUE
)

X: A covariate matrix.
intermediate_q_feature: Whether to use the intermediate quantiles as an additional covariate, by appending it to the X matrix (bool).
intermediate_quantiles: The intermediate conditional quantiles.
X_scaling: Existing "X_scaling" object containing the precomputed mean and variance for each covariate. This enables reusing the scaling choice and parameters from the train set, if computing the excesses on a validation or test set, in order to avoid overfitting. This is performed automatically in the "EQRN" objects.
scale_features: Whether to rescale each input covariates to zero mean and unit variance before applying the network (recommended). If X_scaling is given, X_scaling$scaling overrides scale_features.

Named list containing:

X_excesses: the (possibly rescaled and q_feat transformed) covariate matrix,
X_scaling: object of class "X_scaling" to use for consistent scaling on future datasets.