sklearn.datasets.fetch_covtype

sklearn.datasets.fetch_covtype(data_home=None, download_if_missing=True, random_state=None, shuffle=False, return_X_y=False)[source]

Load the covertype dataset (classification).

Download it if necessary.

Classes 7
Samples total 581012
Dimensionality 54
Features int

Read more in the User Guide.

Parameters:
data_home : string, optional

Specify another download and cache folder for the datasets. By default all scikit-learn data is stored in ‘~/scikit_learn_data’ subfolders.

download_if_missing : boolean, default=True

If False, raise a IOError if the data is not locally available instead of trying to download the data from the source site.

random_state : int, RandomState instance or None (default)

Determines random number generation for dataset shuffling. Pass an int for reproducible output across multiple function calls. See Glossary.

shuffle : bool, default=False

Whether to shuffle dataset.

return_X_y : boolean, default=False.

If True, returns (data.data, data.target) instead of a Bunch object.

New in version 0.20.

Returns:
dataset : dict-like object with the following attributes:
dataset.data : numpy array of shape (581012, 54)

Each row corresponds to the 54 features in the dataset.

dataset.target : numpy array of shape (581012,)

Each value corresponds to one of the 7 forest covertypes with values ranging between 1 to 7.

dataset.DESCR : string

Description of the forest covertype dataset.

(data, target) : tuple if return_X_y is True

New in version 0.20.