FittedGridSearch is an object containing fitted predictive models across
a tuning grid of hyper-parameters returned by GridSearch$fit() as well as
relevant model information such as the best performing model, best
hyper-parameters, etc.
best_idxAn integer specifying the index of $models that
contains the best-performing model.
best_metricThe performance metric of the best model on the validation data.
best_modelThe best performing predictive model.
best_paramsA named list of the hyper-parameters that result in the optimal predictive model.
tune_paramsData.frame of the full hyper-parameter grid.
modelsList of predictive models at every value of $tune_params.
metricsNumeric list; Cross-validation performance metrics on each fold.
predictionsA list containing the predicted hold-out values on every fold.
new()Create a new FittedGridSearch object.
FittedGridSearch$new(tune_params, models, metrics, predictions, optimize_score)tune_paramsData.frame of the full hyper-parameter grid.
modelsList of predictive models at every value of $tune_params.
metricsList of performance metrics on the validation data for
every model in $models.
predictionsA list containing the predicted values on the
validation data for every model in $models.
optimize_scoreEither "max" or "min" indicating whether or not the specified performance metric was maximized or minimized to find the optimal predictive model.
An object of class FittedGridSearch.
clone()The objects of this class are cloneable with this method.
FittedGridSearch$clone(deep = FALSE)deepWhether to make a deep clone.