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).


  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 Description
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.


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.

See Also

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