tf.keras.datasets.reuters.load_data(
path='reuters.npz',
num_words=None,
skip_top=0,
maxlen=None,
test_split=0.2,
seed=113,
start_char=1,
oov_char=2,
index_from=3,
**kwargs
)
Defined in tensorflow/python/keras/datasets/reuters.py
.
Loads the Reuters newswire classification dataset.
Arguments:
path
: where to cache the data (relative to~/.keras/dataset
).num_words
: max number of words to include. Words are ranked by how often they occur (in the training set) and only the most frequent words are keptskip_top
: skip the top N most frequently occurring words (which may not be informative).maxlen
: truncate sequences after this length.test_split
: Fraction of the dataset to be used as test data.seed
: random seed for sample shuffling.start_char
: The start of a sequence will be marked with this character. Set to 1 because 0 is usually the padding character.oov_char
: words that were cut out because of thenum_words
orskip_top
limit will be replaced with this character.index_from
: index actual words with this index and higher.**kwargs
: Used for backwards compatibility.
Returns:
Tuple of Numpy arrays: `(x_train, y_train), (x_test, y_test)`.
Note that the 'out of vocabulary' character is only used for
words that were present in the training set but are not included
because they're not making the num_words
cut here.
Words that were not seen in the training set but are in the test set
have simply been skipped.