| evaluating {TSPred} | R Documentation |
Prediction/modeling quality evaluation
Description
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.
Usage
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 |
... |
Other parameters to be encapsulated in the class object. |
subclass |
Name of new specialized subclass object created in case it is provided. |
Value
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 |
Author(s)
Rebecca Pontes Salles
See Also
Other constructors:
ARIMA(),
LT(),
MSE_eval(),
modeling(),
processing(),
tspred()
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)