Reuters newswire topics classification

Dataset of 11,228 newswires from Reuters, labeled over 46 topics. As with dataset_imdb() , each wire is encoded as a sequence of word indexes (same conventions).

dataset_reuters(path = "reuters.npz", num_words = NULL, skip_top = 0L,
  maxlen = NULL, test_split = 0.2, seed = 113L, start_char = 1L,
  oov_char = 2L, index_from = 3L)

dataset_reuters_word_index(path = "reuters_word_index.pkl")

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 kept
skip_top

Skip the top N most frequently occuring 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 the num_words or skip_top limit will be replaced with this character.
index_from

index actual words with this index and higher.

Value

Lists of training and test data: train$x, train$y, test$x, test$y with same format as dataset_imdb(). The dataset_reuters_word_index() function returns a list where the names are words and the values are integer. e.g. word_index[["giraffe"]] might return 1234.

[["giraffe"]: R:[

See also

Other datasets: dataset_boston_housing, dataset_cifar100, dataset_cifar10, dataset_fashion_mnist, dataset_imdb, dataset_mnist