Allows to manage the executed M.L. models.
new()Method for initializing the object arguments during runtime.
ExecutedModels$new(dir.path)dir.pathThe location were the executed models will be saved.
getNames()The function is used to obtain the name of the ML model achieved the best performance during training stage.
ExecutedModels$getNames()getBest()The function is responsible of returning the model achieving the best performance value during training stage.
ExecutedModels$getBest()A Model object.
add()The function inserts a new model to the list of executed models.
ExecutedModels$add(model, keep.best = TRUE)modelA previously trained model (in Model object).
keep.bestA logical value to define the saving operation. If TRUE only saves the best model, otherwise all executed models are saved.
exist()The function is used to discern if a specific model has been executed previously.
ExecutedModels$exist(model.name)model.nameA character vector with the name of the model to check for existence.
size()The function is used to compute the number of executed ML models.
ExecutedModels$size()A numeric vector or size 1.
save()The function is responsible of saving the information of all executed models into a hidden file.
ExecutedModels$save()
delete()The function removes an specific model.
ExecutedModels$delete(model.name)model.nameA character vector with the name of the model to be removed.
clone()The objects of this class are cloneable with this method.
ExecutedModels$clone(deep = FALSE)deepWhether to make a deep clone.
Model