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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.

Public fields

best_idx

An integer specifying the index of $models that contains the best-performing model.

best_metric

The performance metric of the best model on the validation data.

best_model

The best performing predictive model.

best_params

A named list of the hyper-parameters that result in the optimal predictive model.

tune_params

Data.frame of the full hyper-parameter grid.

models

List of predictive models at every value of $tune_params.

metrics

Numeric list; Cross-validation performance metrics on each fold.

predictions

A list containing the predicted hold-out values on every fold.

Methods


Method new()

Create a new FittedGridSearch object.

Usage

FittedGridSearch$new(tune_params, models, metrics, predictions, optimize_score)

Arguments

tune_params

Data.frame of the full hyper-parameter grid.

models

List of predictive models at every value of $tune_params.

metrics

List of performance metrics on the validation data for every model in $models.

predictions

A list containing the predicted values on the validation data for every model in $models.

optimize_score

Either "max" or "min" indicating whether or not the specified performance metric was maximized or minimized to find the optimal predictive model.

Returns

An object of class FittedGridSearch.


Method clone()

The objects of this class are cloneable with this method.

Usage

FittedGridSearch$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.