dataset_reuters: Reuters newswire topics classification

In dfalbel/keras: R Interface to 'Keras'

Description

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).

Usage

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.

See Also

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

dfalbel/keras documentation built on Nov. 27, 2019, 8:16 p.m.