evaluating function

Prediction/modeling quality evaluation

Prediction/modeling quality evaluation

Constructor for the evaluating class representing a time series prediction or modeling fitness quality evaluation based on a particular metric. The evaluating class has two specialized subclasses fitness and error reagarding fitness criteria and prediction/modeling error metrics, respectively.

evaluating(eval_func, eval_par = NULL, ..., subclass = NULL) fitness(eval_func, eval_par = NULL, ..., subclass = NULL) error(eval_func, eval_par = NULL, ..., subclass = NULL)

Arguments

  • eval_func: A function for computing a particular metric.
  • eval_par: List of named parameters required by eval_func.
  • ...: Other parameters to be encapsulated in the class object.
  • subclass: Name of new specialized subclass object created in case it is provided.

Returns

An object of class evaluating. A list usually containing at least the following elements: - func: A function for computing a particular metric.

  • par: Particular parameters required by func.

Examples

e <- error(eval_func=TSPred::NMSE, eval_par=list(train.actual=NULL), method="Normalised Mean Squared Error", subclass="NMSE") summary(e) f <- fitness(eval_func=stats::AIC, method="Akaike's Information Criterion", subclass="AIC") summary(f)

See Also

Other constructors: ARIMA(), LT(), MSE_eval(), modeling(), processing(), tspred()

Author(s)

Rebecca Pontes Salles

  • Maintainer: Rebecca Pontes Salles
  • License: GPL (>= 2)
  • Last published: 2021-01-21