as_tuned: convert tskrr models

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

Description

These functions allow converting models that inherit from the tskrr and tskrrTune class into each other, keeping track of whether the model is homogeneous or heterogeneous. The dots argument allows specifying values for possible extra slots when converting from tskrr to tskrrTune. More information on these slots can be found on the help page of tskrrTune. These functions are not exported.

Usage

as_tuned(x, ...)

as_tskrr(x, ...)

## S4 method for signature 'tskrrHomogeneous'
as_tuned(x, ...)

## S4 method for signature 'tskrrHeterogeneous'
as_tuned(x, ...)

## S4 method for signature 'tskrrTune'
as_tskrr(x)

## S4 method for signature 'tskrrImpute'
as_tskrr(x)

## S4 method for signature 'tskrr'
as_tskrr(x)

Arguments

x	a model of class tskrr
...	values for the extra slots defined by the class tskrrTune

Value

For as_tuned: a tskrrTune object of the proper class (homogeneous or heterogeneous)

For as_tskrr: an object of class tskrrHomogeneous or tskrrHeterogeneous depending on whether the original object was homogeneous or heterogeneous.

Warning

This functions do NOT tune a model. they are used internally to make the connection between both types in the methods.

See Also

• tune for actually tuning a model.

• tskrrTune for names and possible values of the slots passed through ...

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