prediction.nonsplit.result: Internal lassoenet functions
In MokyoZhou/lassoenet: An Interactive Implementation of Penalised Regressions

Description Usage Arguments Value Details Author(s)

Internal lassoenet functions

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prediction.nonsplit.result(best.lasso.result = best.lasso.result,
  best.EN.result = best.EN.result, data = data, x.indices = x.indices,
  response = response, alph = alph, parallel = parallel)

`best.lasso.result`	A vector contains the outputs from the function `prediction_Lasso`.
`best.EN.result`	A vector contains the outputs from the function `prediction_ElasticNet`.
`data`	A well-cleaned `data.frame`.
`x.indices`	Locations of the predictors within the `data.frame`.
`response`	Location of the response within the `data.frame`.
`alph`	An internal argument.
`parallel`	Parallelsation.

A vector of outputs and some plots related to the best model.

These are not intended for use by users. This function provides an automatic comparison between the Lasso and the Elastic Net model based on the Mean squared errors of these models. The return from this function will then enter the penalised_pred function.

Mokyo Zhou

MokyoZhou/lassoenet documentation built on May 20, 2019, 11:38 a.m.