The class tskrrTune represents a tuned
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.
a list object with the elements
k and possibly
g indicating the tested lambda values for the row kernel
and - if applicable - the column kernel
G. Both elements have
to be numeric.
a numeric value with the loss associated with the best lambdas
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)
the used loss function
a character value describing the exclusion used
a logical value indicating whether or not the cross validation replaced the excluded values by zero
a logical value indicating whether the grid search was done in one dimension. For homogeneous networks, this is true by default.
tune for the tuning itself
tskrrTuneHeterogeneous for the actual classes.
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