The class tskrrTune represents a tuned `tskrr`

model, and is the output of the function `tune`

. Apart from
the model, it contains extra information on the tuning procedure. This is
a virtual class only.

`lambda_grid`

a list object with the elements

`k`

and possibly`g`

indicating the tested lambda values for the row kernel`K`

and - if applicable - the column kernel`G`

. Both elements have to be numeric.`best_loss`

a numeric value with the loss associated with the best lambdas

`loss_values`

a matrix with the loss results from the searched grid. The rows form the X dimension (related to the first lambda), the columns form the Y dimension (related to the second lambda if applicable)

`loss_function`

the used loss function

`exclusion`

a character value describing the exclusion used

`replaceby0`

a logical value indicating whether or not the cross validation replaced the excluded values by zero

`onedim`

a logical value indicating whether the grid search was done in one dimension. For homogeneous networks, this is true by default.

the function

`tune`

for the tuning itselfthe class

`tskrrTuneHomogeneous`

and`tskrrTuneHeterogeneous`

for the actual classes.

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