class openml.tasks.OpenMLLearningCurveTask(task_type_id: openml.tasks.task.TaskType, task_type: str, data_set_id: int, target_name: str, estimation_procedure_id: int = 13, estimation_procedure_type: Optional[str] = None, estimation_parameters: Optional[Dict[str, str]] = None, data_splits_url: Optional[str] = None, task_id: Optional[int] = None, evaluation_measure: Optional[str] = None, class_labels: Optional[List[str]] = None, cost_matrix: Optional[numpy.ndarray] = None)

OpenML Learning Curve object.

download_split() openml.tasks.split.OpenMLSplit

Download the OpenML split for a given task.

get_X_and_y(dataset_format: str = 'array') Tuple[Union[numpy.ndarray, pandas.core.frame.DataFrame, scipy.sparse.base.spmatrix], Union[numpy.ndarray, pandas.core.series.Series]]

Get data associated with the current task.


Data structure of the returned data. See openml.datasets.OpenMLDataset.get_data() for possible options.

tuple - X and y
get_dataset() openml.datasets.dataset.OpenMLDataset

Download dataset associated with task

property id: Optional[int]

The id of the entity, it is unique for its entity type.


Opens the OpenML web page corresponding to this object in your default browser.

property openml_url: Optional[str]

The URL of the object on the server, if it was uploaded, else None.

push_tag(tag: str)

Annotates this entity with a tag on the server.


Tag to attach to the flow.

remove_tag(tag: str)

Removes a tag from this entity on the server.


Tag to attach to the flow.

classmethod url_for_id(id_: int) str

Return the OpenML URL for the object of the class entity with the given id.