sklearn.datasets.fetch_kddcup99(subset=None, data_home=None, shuffle=False, random_state=None, percent10=True, download_if_missing=True, return_X_y=False)[source]

Load the kddcup99 dataset (classification).

Download it if necessary.

Classes 23
Samples total 4898431
Dimensionality 41
Features discrete (int) or continuous (float)

Read more in the User Guide.

New in version 0.18.

subset : None, ‘SA’, ‘SF’, ‘http’, ‘smtp’

To return the corresponding classical subsets of kddcup 99. If None, return the entire kddcup 99 dataset.

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. .. versionadded:: 0.19

shuffle : bool, default=False

Whether to shuffle dataset.

random_state : int, RandomState instance or None (default)

Determines random number generation for dataset shuffling and for selection of abnormal samples if subset=’SA’. Pass an int for reproducible output across multiple function calls. See Glossary.

percent10 : bool, default=True

Whether to load only 10 percent of the data.

download_if_missing : bool, 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.

return_X_y : boolean, default=False.

If True, returns (data, target) instead of a Bunch object. See below for more information about the data and target object.

New in version 0.20.

data : Bunch
Dictionary-like object, the interesting attributes are:
  • ‘data’, the data to learn.
  • ‘target’, the regression target for each sample.
  • ‘DESCR’, a description of the dataset.
(data, target) : tuple if return_X_y is True

New in version 0.20.