update.qreg_lightgbm: Model update (retraining) method for Multiple Quantile...

In jbrowell/ProbCast: Flexible Probabilistic Forecasting

Model update (retraining) method for Multiple Quantile Regression from lightgbm Gradient Boosted Decision Trees.

Description

This function returns updated fitted qreg_lightgbm models, which are the supplied previously fitted models updated with new data. S3 Method for qreg_lightgbm objects

Usage

update.qreg_lightgbm(
  object,
  newdata,
  model_name = NULL,
  pckgs = NULL,
  cores = 1
)

Arguments

object	fitted model of class qreg_lightgbm obtained from the function qreg_lightgbm().
newdata	data.frame of new observations for which to update the model fit
model_name	the name of the model to be used for prediction. Unless specified, object$default_model is used.
pckgs	specify additional packages required for each worker (e.g. c("data.table") if data stored as such).
cores	the number of available cores. Defaults to one, i.e. no parallelisation, although in this case the user must still specify pckgs if applicable.
...	additional arguments; not currently used.

Details

this function updates the fitted lightgbm model with the supplied new data. NOTE predictions saved within the lightgbm object are not updated within this function.

Value

a named list containing fitted models as a list of qreg_lightgbm objects.

Author(s)

Gordon McFadzean, [e-mail]

jbrowell/ProbCast documentation built on July 20, 2024, 1:53 p.m.