learning_base_models {tsensembler} | R Documentation |
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 |
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
Examples
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)
[Package tsensembler version 0.1.0 Index]