skdatasets.repositories.raetsch.fetch

skdatasets.repositories.raetsch.fetch(name: str, data_home: Optional[str] = None, *, return_X_y: Literal[False] = False) → Bunch[source]
skdatasets.repositories.raetsch.fetch(name: str, data_home: Optional[str] = None, *, return_X_y: Literal[True]) → Tuple[ndarray[Any, dtype[float]], ndarray[Any, dtype[Union[int, float]]]]

Fetch Gunnar Raetsch’s dataset.

Fetch a Gunnar Raetsch’s benchmark dataset by name. Availabe datasets are ‘banana’, ‘breast_cancer’, ‘diabetis’, ‘flare_solar’, ‘german’, ‘heart’, ‘image’, ‘ringnorm’, ‘splice’, ‘thyroid’, ‘titanic’, ‘twonorm’ and ‘waveform’. More info at https://github.com/tdiethe/gunnar_raetsch_benchmark_datasets.

Parameters:

  • name (string) – Dataset name.

  • data_home (string or None, default None) – Specify another download and cache folder for the data sets. By default all scikit-learn data is stored in ‘~/scikit_learn_data’ subfolders.

  • return_X_y (bool, default=False) – If True, returns (data, target) instead of a Bunch object.

Returns:

  • data (Bunch) – Dictionary-like object with all the data and metadata.

  • (data, target) (tuple if return_X_y is True)