tsensembler (version 0.1.0)

learning_base_models: Training the base models of an ensemble

Description

This function uses train to build a set of predictive models, according to specs

Usage

learning_base_models(train, form, specs, num_cores)

Arguments

train

training set to build the predictive models;

form

formula;

specs

object of class model_specs-class

num_cores

A numeric value to specify the number of cores used to train base and meta models. num_cores = 1 leads to sequential training of models. num_cores > 1 splits the training of the base models across num_cores cores.

Value

A series of predictive models (base_model), and the weights of the models computed in the training data (preweights).

See Also

build_base_ensemble.

Examples

# NOT RUN {
data("water_consumption")
dataset <- embed_timeseries(water_consumption, 5)
specs <- model_specs(c("bm_ppr","bm_svr"), NULL)
M <- build_base_ensemble(target ~., dataset, specs, 1)

# }