This is a dataset of 11,228 newswires from Reuters, labeled over 46 topics.
This was originally generated by parsing and preprocessing the classic
Reuters-21578 dataset, but the preprocessing code is no longer packaged
with Keras. See this
GitHub discussion
for more info.
Each newswire is encoded as a list of word indexes (integers).
For convenience, words are indexed by overall frequency in the dataset,
so that for instance the integer "3" encodes the 3rd most frequent word in
the data. This allows for quick filtering operations such as:
"only consider the top 10,000 most
common words, but eliminate the top 20 most common words".
As a convention, "0" does not stand for a specific word, but instead is used
to encode any unknown word.
Args
path
where to cache the data (relative to ~/.keras/dataset).
num_words
integer or None. Words are
ranked by how often they occur (in the training set) and only
the num_words most frequent words are kept. Any less frequent word
will appear as oov_char value in the sequence data. If None,
all words are kept. Defaults to None.
skip_top
skip the top N most frequently occurring words
(which may not be informative). These words will appear as
oov_char value in the dataset. 0 means no words are
skipped. Defaults to 0.
maxlen
int or None. Maximum sequence length.
Any longer sequence will be truncated. None means no truncation.
Defaults to None.
test_split
Float between 0. and 1.. Fraction of the dataset to be
used as test data. 0.2 means that 20% of the dataset is used as
test data. Defaults to 0.2.
seed
int. Seed for reproducible data shuffling.
start_char
int. The start of a sequence will be marked with this
character. 0 is usually the padding character. Defaults to 1.
oov_char
int. The out-of-vocabulary character.
Words that were cut out because of the num_words or
skip_top limits will be replaced with this character.
index_from
int. 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).
x_train, x_test: lists of sequences, which are lists of indexes
(integers). If the num_words argument was specific, the maximum
possible index value is num_words - 1. If the maxlen argument was
specified, the largest possible sequence length is maxlen.
y_train, y_test: lists of integer labels (1 or 0).
[[["Easy to understand","easyToUnderstand","thumb-up"],["Solved my problem","solvedMyProblem","thumb-up"],["Other","otherUp","thumb-up"]],[["Missing the information I need","missingTheInformationINeed","thumb-down"],["Too complicated / too many steps","tooComplicatedTooManySteps","thumb-down"],["Out of date","outOfDate","thumb-down"],["Samples / code issue","samplesCodeIssue","thumb-down"],["Other","otherDown","thumb-down"]],["Last updated 2023-10-06 UTC."],[],[]]