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
- subsetNone, ‘SA’, ‘SF’, ‘http’, ‘smtp’
To return the corresponding classical subsets of kddcup 99. If None, return the entire kddcup 99 dataset.
- data_homestring, 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
- shufflebool, default=False
Whether to shuffle dataset.
- random_stateint, RandomState instance, default=None
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.- percent10bool, default=True
Whether to load only 10 percent of the data.
- download_if_missingbool, 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_yboolean, default=False.
If True, returns
(data, target)
instead of a Bunch object. See below for more information about thedata
andtarget
object.New in version 0.20.
- Returns
- data
Bunch
Dictionary-like object, with the following attributes.
- datandarray of shape (494021, 41)
The data matrix to learn.
- targetndarray of shape (494021,)
The regression target for each sample.
- DESCRstr
The full description of the dataset.
- (data, target)tuple if
return_X_y
is True New in version 0.20.
- data