Load the kddcup99 dataset (classification).
Download it if necessary.
Read more in the User Guide.
Added in version 0.18.
To return the corresponding classical subsets of kddcup 99. If None, return the entire kddcup 99 dataset.
Specify another download and cache folder for the datasets. By default all scikit-learn data is stored in ‘~/scikit_learn_data’ subfolders.
Added in version 0.19.
Whether to shuffle dataset.
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.
Whether to load only 10 percent of the data.
If False, raise an OSError if the data is not locally available instead of trying to download the data from the source site.
If True, returns (data, target)
instead of a Bunch object. See below for more information about the data
and target
object.
Added in version 0.20.
If True
, returns a pandas Dataframe for the data
and target
objects in the Bunch
returned object; Bunch
return object will also have a frame
member.
Added in version 0.24.
Number of retries when HTTP errors are encountered.
Added in version 1.5.
Number of seconds between retries.
Added in version 1.5.
Bunch
Dictionary-like object, with the following attributes.
The data matrix to learn. If as_frame=True
, data
will be a pandas DataFrame.
The regression target for each sample. If as_frame=True
, target
will be a pandas Series.
Only present when as_frame=True
. Contains data
and target
.
The full description of the dataset.
The names of the dataset columns
The names of the target columns
return_X_y
is True
A tuple of two ndarray. The first containing a 2D array of shape (n_samples, n_features) with each row representing one sample and each column representing the features. The second ndarray of shape (n_samples,) containing the target samples.
Added in version 0.20.
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