fetch_20newsgroups #

sklearn.datasets.fetch_20newsgroups(*,data_home=None,subset='train',categories=None,shuffle=True,random_state=42,remove=(),download_if_missing=True,return_X_y=False,n_retries=3,delay=1.0)[source]#

Load the filenames and data from the 20 newsgroups dataset (classification).

Download it if necessary.

Classes	20
Samples total	18846
Dimensionality	1
Features	text

Read more in theUser Guide.

Parameters:

data_homestr or path-like, default=None

Specify a download and cache folder for the datasets. If None,all scikit-learn data is stored in ‘~/scikit_learn_data’ subfolders.

subset{‘train’, ‘test’, ‘all’}, default=’train’

Select the dataset to load: ‘train’ for the training set, ‘test’for the test set, ‘all’ for both, with shuffled ordering.

categoriesarray-like, dtype=str, default=None

If None (default), load all the categories.If not None, list of category names to load (other categoriesignored).

shufflebool, default=True

Whether or not to shuffle the data: might be important for models thatmake the assumption that the samples are independent and identicallydistributed (i.i.d.), such as stochastic gradient descent.

random_stateint, RandomState instance or None, default=42

Determines random number generation for dataset shuffling. Pass an intfor reproducible output across multiple function calls.SeeGlossary.

removetuple, default=()

May contain any subset of (‘headers’, ‘footers’, ‘quotes’). Each ofthese are kinds of text that will be detected and removed from thenewsgroup posts, preventing classifiers from overfitting onmetadata.

‘headers’ removes newsgroup headers, ‘footers’ removes blocks at theends of posts that look like signatures, and ‘quotes’ removes linesthat appear to be quoting another post.

‘headers’ follows an exact standard; the other filters are not alwayscorrect.

download_if_missingbool, default=True

If False, raise an OSError if the data is not locally availableinstead of trying to download the data from the source site.

return_X_ybool, default=False

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

Added in version 0.22.

n_retriesint, default=3

Number of retries when HTTP errors are encountered.

Added in version 1.5.

delayfloat, default=1.0

Number of seconds between retries.

Added in version 1.5.

Returns:

bunchBunch

Dictionary-like object, with the following attributes.

datalist of shape (n_samples,): The data list to learn.
target: ndarray of shape (n_samples,): The target labels.
filenames: list of shape (n_samples,): The path to the location of the data.
DESCR: str: The full description of the dataset.
target_names: list of shape (n_classes,): The names of target classes.

(data, target)tuple ifreturn_X_y=True

A tuple of two ndarrays. The first contains a 2D array of shape(n_samples, n_classes) with each row representing one sample and eachcolumn representing the features. The second array of shape(n_samples,) contains the target samples.

Added in version 0.22.

Examples

>>>fromsklearn.datasetsimportfetch_20newsgroups>>>cats=['alt.atheism','sci.space']>>>newsgroups_train=fetch_20newsgroups(subset='train',categories=cats)>>>list(newsgroups_train.target_names)['alt.atheism', 'sci.space']>>>newsgroups_train.filenames.shape(1073,)>>>newsgroups_train.target.shape(1073,)>>>newsgroups_train.target[:10]array([0, 1, 1, 1, 0, 1, 1, 0, 0, 0])