Visualize model as interactive surface

This class is used to create interactive 3D surface visualizations of learners and tasks for 2D input data using plotly.

Super classes

vistool::Visualizer -> vistool::VisualizerSurface -> VisualizerSurfaceModel

Public fields

task

(mlr3::Task)
Task used to train the model.

learner

(mlr3::Learner)
Learner used to train the model.

Methods

Public methods

• VisualizerSurfaceModel$new()

• VisualizerSurfaceModel$add_training_data()

• VisualizerSurfaceModel$add_boundary()

• VisualizerSurfaceModel$plot()

• VisualizerSurfaceModel$clone()

Inherited methods

• vistool::Visualizer$add_annotation()
• vistool::Visualizer$add_points()
• vistool::Visualizer$resolve_layer_colors()
• vistool::Visualizer$save()
• vistool::Visualizer$set_theme()
• vistool::Visualizer$theme()
• vistool::VisualizerSurface$add_contours()
• vistool::VisualizerSurface$init_layer_contour()
• vistool::VisualizerSurface$init_layer_surface()
• vistool::VisualizerSurface$set_layout()
• vistool::VisualizerSurface$set_scene()

---

Method new()

Creates a new instance of this R6 class.

Usage

VisualizerSurfaceModel$new(
  task,
  learner,
  x1_limits = NULL,
  x2_limits = NULL,
  padding = 0,
  n_points = 100L,
  hypothesis = NULL,
  domain = NULL,
  retrain = TRUE
)

Arguments

task

(mlr3::Task)
The task to train the model on.

learner

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

x1_limits

(numeric(2))
The x1 limits.

x1_limits

(numeric(2))
The x1 limits.

x2_limits

(numeric(2))
The x2 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.

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.

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.

hypothesis

(Hypothesis|NULL) Optional hypothesis used instead of a learner

domain

(list|NULL) Domain limits when visualizing a hypothesis without a task

retrain

(logical(1)) Whether to retrain the learner if it has already been trained on the task. Default is TRUE.

---

Method add_training_data()

Adds the training data to the plot.

Usage

VisualizerSurfaceModel$add_training_data(
  size = NULL,
  color = "auto",
  shape = 0,
  ...
)

Arguments

size

(numeric(1))
Size of the points. If NULL, uses theme$point_size. Default is NULL.

color

(character(1) or named character)
Color of the points. For classification tasks:

• character(1): A single color for all points (e.g., "blue") or "auto" for automatic color assignment.

• named character: A vector mapping class labels to colors (e.g., c(pos = "red", neg = "blue")). For regression tasks, only single colors are supported. Default is "auto".

shape

(numeric(1) or named numeric)
Shape/symbol of the points. For classification tasks:

• numeric(1): A single symbol for all points (e.g., 0 for circle).

• named numeric: A vector mapping class labels to symbols (e.g., c(pos = 0, neg = 1)). For regression tasks, only single symbols are supported. Default is 0 (circle).

...

(any)
Further arguments passed to add_trace(...).

---

Method add_boundary()

Adds boundary surface(s) to the plot at specified values.

Usage

VisualizerSurfaceModel$add_boundary(values = NULL, color = NULL, ...)

Arguments

values

(numeric())
Vector of z-values where to draw boundary surfaces. For classification with probability predictions, defaults to 0.5. For regression or response predictions, defaults to the median of predictions.

color

(character(1) or list())
Color specification for boundary surfaces. Default uses a neutral colorscale.

...

(any)
Further arguments passed to add_trace(...) or add_surface(...).

---

Method plot()

Create and return the plotly plot with model-specific layers.

Usage

VisualizerSurfaceModel$plot(...)

Arguments

...

Additional arguments passed to the parent plot method.

Returns

A plotly object.

---

Method clone()

The objects of this class are cloneable with this method.

Usage

VisualizerSurfaceModel$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.