Auto Class

This class is the base class for all autos.

Public fields

id

(character(1)).

properties

(character()).

task_types

(character()).

packages

(character()).

devices

(character()).

Methods

Public methods

• Auto$new()

• Auto$check()

• Auto$graph()

• Auto$early_stopping_rounds()

• Auto$estimate_memory()

• Auto$finalize_model()

• Auto$design_default()

• Auto$design_set()

• Auto$search_space()

• Auto$clone()

---

Method new()

Creates a new instance of this R6 class.

Usage

Auto$new(
  id,
  properties = character(0),
  task_types = character(0),
  packages = character(0),
  devices = character(0)
)

Arguments

id

(character(1)).

properties

(character()).

task_types

(character()).

packages

(character()).

devices

(character()).

---

Method check()

Check if the auto is compatible with the task.

Usage

Auto$check(task, memory_limit = Inf, large_data_set = FALSE, devices)

Arguments

task

(mlr3::Task).

memory_limit

(integer(1)).

large_data_set

(logical(1)).

devices

(character())
Devices to use. Allowed values are "cpu" and "cuda". Default is "cpu".

---

Method graph()

Create the graph for the auto.

Usage

Auto$graph(task, measure, n_threads, timeout, devices)

Arguments

task

(mlr3::Task).

measure

(mlr3::Measure).

n_threads

(integer(1)).

timeout

(integer(1)).

devices

(character())
Devices to use. Allowed values are "cpu" and "cuda". Default is "cpu".

---

Method early_stopping_rounds()

Estimate the number of early stopping rounds.

Usage

Auto$early_stopping_rounds(task)

Arguments

task

(mlr3::Task).

---

Method estimate_memory()

Estimate the memory for the auto.

Usage

Auto$estimate_memory(task)

Arguments

task

(mlr3::Task).

---

Method finalize_model()

Prepare the graph learner for the final model fit. Called after tuning to undo tuning-only setup (e.g., timeout callbacks).

Usage

Auto$finalize_model(graph_learner)

Arguments

graph_learner

(mlr3pipelines::GraphLearner).

---

Method design_default()

Default hyperparameters for the learner.

Usage

Auto$design_default(task)

Arguments

task

(mlr3::Task).

---

Method design_set()

Get the initial hyperparameter set for the learner.

Usage

Auto$design_set(task, measure, size)

Arguments

task

(mlr3::Task).

measure

(mlr3::Measure).

size

(integer(1)).

---

Method search_space()

Get the search space for the learner.

Usage

Auto$search_space(task)

Arguments

task

(mlr3::Task).

---

Method clone()

The objects of this class are cloneable with this method.

Usage

Auto$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.