tsensembler (version 0.0.5)

build_base_ensemble: Wrapper for creating an ensemble

Description

Using the parameter specifications from model_specs-class, this function trains a set of regression models.

Usage

build_base_ensemble(form, data, specs, num_cores = 1)

Arguments

form

formula;

data

data.frame for training the predictive models;

specs

object of class model_specs-class. Contains the information about the parameter setting of the models to train.

num_cores

number of cores

Value

An S4 class with the following slots: base_models, a list containing the trained models; pre_weights, a numeric vector describing the weights of the base models according to their performance in the training data; and colnames, the column names of the data, used for reference.

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)

# }