sklearn.datasets.fetch_kddcup99

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.

Parameters:

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.

Returns:

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.