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This function converts to a visualizer.

Usage

as_visualizer(x, ...)

# S3 method for Task
as_visualizer(
  x,
  learner,
  x1_limits = NULL,
  x2_limits = NULL,
  padding = 0,
  n_points = 100L,
  ...
)

# S3 method for Objective
as_visualizer(
  x,
  x1_limits = NULL,
  x2_limits = NULL,
  padding = 0,
  n_points = 100L,
  ...
)

# S3 method for LossFunction
as_visualizer(x, y_pred, y_true, ...)

Arguments

x

(`any`)
Object to convert to a visualizer.

...

(`any`)
Additional arguments.

learner

(`mlr3::Learner`)
The learner to train the model with.

x1_limits

(`numeric(2)`)
The x1 limits.

x2_limits

(`numeric(2)`)
The x2 limits.

padding

(`numeric(1)`)
A margin that is added to x1limits and x2limits. The x1 margin is calculated by `max(x1lmits) - min(x1limits) * padding`.

n_points

(`integer(1)`)
The number of generated point per dimension. Note that a grid of `npoints^2` values is generated and evaluated by `objective$eval(x)` to plot the surface.

y_pred

(`numeric()`)
Predicted values.

y_true

(`numeric(1)`)
True value.