Skip to contents

Provide a summary of the hyperparameter tuning

Source: R/methods-base.R
summary.tune_esn.Rd

Provide a summary of the tuned hyperparameters alpha, rho and tau.

Usage

# S3 method for class 'tune_esn'
summary(object, metric = "mse", ...)

Arguments

object

An object of class tune_esn. The result of a call to tune_esn().

metric

Character value. The metric used to select the best hyperparameter combination (metric = c("mse", "mae").

...

Currently not in use.

Value

Print detailed model summary.

See also

Other base functions: forecast_esn(), is.esn(), is.forecast_esn(), is.tune_esn(), plot.esn(), plot.forecast_esn(), plot.tune_esn(), print.esn(), summary.esn(), train_esn(), tune_esn()

Examples

xdata <- as.numeric(AirPassengers)
fit <- tune_esn(
  y = xdata,
  n_ahead = 12,
  n_split = 5,
  alpha = c(0.5, 1),
  rho   = c(1.0),
  tau   = c(0.4),
  inf_crit = "bic"
)

summary(fit)
#> # A tibble: 5 × 11
#>   alpha   rho   tau split train_start train_end test_start test_end   mse   mae
#>   <dbl> <dbl> <dbl> <int>       <int>     <int>      <int>    <int> <dbl> <dbl>
#> 1     1     1   0.4     1           1        84         85       96  471.  19.5
#> 2     1     1   0.4     2           1        96         97      108  376.  14.2
#> 3     1     1   0.4     3           1       108        109      120  526.  19.0
#> 4     1     1   0.4     4           1       120        121      132  547.  20.2
#> 5     1     1   0.4     5           1       132        133      144  396.  17.0
#> # ℹ 1 more variable: id <int>