trafoensemble: Transformation ensembles

Description

Transformation ensembles

Usage

trafoensemble(
  formula,
  data,
  n_ensemble = 5,
  verbose = FALSE,
  print_members = TRUE,
  stop_if_nan = TRUE,
  save_weights = TRUE,
  callbacks = list(),
  save_fun = NULL,
  seed = seq_len(n_ensemble),
  tf_seeds = seq_len(n_ensemble),
  ...
)

Value

Ensemble of "deeptrafo" models with list of training histories and fitted weights included in ensemble_results. For details see the return statment in ensemble.

Arguments

formula: Formula specifying the response, interaction, shift terms as response | interacting ~ shifting. auto-regressive transformation models (ATMs).
data: Named list or data.frame which may contain both structured and unstructured data.
n_ensemble: Numeric; number of ensemble members to fit.
verbose: Logical; whether to print training in each fold.
print_members: Logical; print results for each member.
stop_if_nan: Logical; whether to stop ensembling if NaN values occur
save_weights: Logical; whether to save the ensemble weights.
callbacks: List; callbacks used for fitting.
save_fun: Function; function to be applied to each member to be stored in the final result.
seed: Numeric vector of length n_ensemble; seeds for model re-initialization. Changing these seeds does not change the parameters of the interacting predictor coef(obj, which_param = "interacting"), change tf_seeds to adapt those coefficients.
tf_seeds: Numeric vector of length n_ensemble; explicit seed for changing the parameters of the interacting predictor. Distinct from seed which is used for weight re-initialization of the rest of the model (i.e., the shifting predictor and potential neural network components in the interacting component).
...: Further arguments passed to deeptrafo and fit.