sklearn.datasets.load_mlcomp(name_or_id, set_='raw', mlcomp_root=None, **kwargs)[source]

Load a datasets as downloaded from


name_or_id : the integer id or the string name metadata of the MLComp

dataset to load

set_ : select the portion to load: ‘train’, ‘test’ or ‘raw’

mlcomp_root : the filesystem path to the root folder where MLComp datasets

are stored, if mlcomp_root is None, the MLCOMP_DATASETS_HOME environment variable is looked up instead.

**kwargs : domain specific kwargs to be passed to the dataset loader.

Read more in the :ref:`User Guide <datasets>`. :


data : Bunch

Dictionary-like object, the interesting attributes are: ‘filenames’, the files holding the raw to learn, ‘target’, the classification labels (integer index), ‘target_names’, the meaning of the labels, and ‘DESCR’, the full description of the dataset.

Note on the lookup process: depending on the type of name_or_id, :

will choose between integer id lookup or metadata name lookup by :

looking at the unzipped archives and metadata file. :

TODO: implement zip dataset loading too :

Examples using sklearn.datasets.load_mlcomp