tskrrTune-class: Class tskrrTune

In xnet: Two-Step Kernel Ridge Regression for Network Predictions

Description

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.

Slots

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.

See Also

• the function tune for the tuning itself

• the class tskrrTuneHomogeneous and tskrrTuneHeterogeneous for the actual classes.

xnet documentation built on Feb. 4, 2020, 9:10 a.m.