dataset_reuters
Reuters newswire topics classification
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
| 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. |
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()