#' @title Fit One or More Models to a Training Set
#' @param historical_data (`data.frame`) A table where samples are in rows and features are in columns.
#' @param model_formula (`formula`) A symbolic description of the model to be fitted.
#' @note \code{model_fit} has access to variables which were assigned to \code{model_environment}.
#' @return A model object
model_fit <- function(historical_data, model_formula)
{
set.seed(1451)
mdl_obj <- ranger::ranger(
model_formula,
data = historical_data,
verbose = getOption("verbose"),
num.trees = params$num.trees,
mtry = eval(parse(text = params$mtry)),
max.depth = params$max.depth,
sample.fraction = params$sample.fraction,
splitrule = params$splitrule,
num.random.splits = params$num.random.splits,
respect.unordered.factors = params$respect.unordered.factors
)
return(mdl_obj)
}
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