MboPlotFit: MboPlotFit

In PhilippScheller/VisBayesOpt: Visualizing model based optimization runs from package mlrMBO

Description

This class plots the quality of the single models fit in the mbo run.

Super class

VisBayesOpt::MboPlot -> MboPlotFit

Methods

Public methods

• MboPlotFit$new()

• MboPlotFit$plot()

• MboPlotFit$clone()

Inherited methods

• VisBayesOpt::MboPlot$set_param_vals()

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Method new()

Creates a new instance of this R6 class.

Usage

MboPlotFit$new(opt_state)

Arguments

opt_state

(OptState).

---

Method plot()

Plots the fit of the model using R-squared for each iteration of the mbo run.

Usage

MboPlotFit$plot(
  highlight_iter = self$param_vals$highlight_iter,
  predict_y_iter_surrogate = self$param_vals$predict_y_iter_surrogate
)

Arguments

highlight_iter

(integer(1) | NULL)
Specifies the iteration to be highlighted. The default NULL does not highlight any iteration.

predict_y_iter_surrogate

(logical(1) | FALSE)
Specifies if y_hat is predicted with the surrogate from the chosen iteration. If FALSE y_hat is taken from the optimization path, i.e. predicted based on surrogate of the respective iteration. If TRUE we use the surrogate of 'highlight_iter' iteration to predict all points based on the search space x again.

Returns

(ggplot).

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Method clone()

The objects of this class are cloneable with this method.

Usage

MboPlotFit$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.

PhilippScheller/VisBayesOpt documentation built on Sept. 14, 2020, 12:47 p.m.