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mlr3oml (version 0.9.0)

oml_task: Interface to OpenML Tasks

Description

This is the class for tasks served on OpenML. It consists of a dataset and other meta-information such as the target variable for supervised problems. This object can also be constructed using the sugar function otsk().

Arguments

mlr3 Integration

  • Obtain a mlr3::Task by calling as_task().

  • Obtain a mlr3::Resampling by calling as_resampling().

Super class

mlr3oml::OMLObject -> OMLTask

Active bindings

estimation_procedure

(list())
The estimation procedure, returns NULL if none is available.

task_splits

(data.table())
A data.table containing the splits as provided by OpenML.

tags

(character())
Returns all tags of the object.

parquet

(logical(1))
Whether to use parquet.

name

(character(1))
Name of the task, extracted from the task description.

task_type

(character(1))
The OpenML task type.

data_id

(integer())
Data id, extracted from the task description.

data

(OMLData)
Access to the underlying OpenML data set via a OMLData object.

nrow

(integer())
Number of rows, extracted from the OMLData object.

ncol

(integer())
Number of columns, as extracted from the OMLData object.

target_names

(character())
Name of the targets, as extracted from the OpenML task description.

feature_names

(character())
Name of the features (without targets of this OMLTask).

data_name

(character())
Name of the dataset (inferred from the task name).

Methods

Inherited methods

Method new()

Creates a new instance of this R6 class.

Usage

OMLTask$new(
  id,
  parquet = parquet_default(),
  test_server = test_server_default()
)

Arguments

id

(integer(1))
OpenML id for the object.

parquet

(logical(1))
Whether to use parquet instead of arff. If parquet is not available, it will fall back to arff. Defaults to value of option "mlr3oml.parquet" or FALSE if not set.

test_server

(character(1))
Whether to use the OpenML test server or public server. Defaults to value of option "mlr3oml.test_server", or FALSE if not set.

Method print()

Prints the object. For a more detailed printer, convert to a mlr3::Task via $task.

Usage

OMLTask$print()

Method download()

Downloads the whole object for offline usage.

Usage

OMLTask$download()

Method clone()

The objects of this class are cloneable with this method.

Usage

OMLTask$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.

References

Vanschoren J, van Rijn JN, Bischl B, Torgo L (2014). “OpenML.” ACM SIGKDD Explorations Newsletter, 15(2), 49--60. tools:::Rd_expr_doi("10.1145/2641190.2641198").

Examples

Run this code
# For technical reasons, examples cannot be included in this R package.
# Instead, these are some relevant resources:
#
# Large-Scale Benchmarking chapter in the mlr3book:
# https://mlr3book.mlr-org.com/chapters/chapter11/large-scale_benchmarking.html
#
# Package Article:
# https://mlr3oml.mlr-org.com/articles/tutorial.html

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