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I use reuters dataset in Keras.
And I want to know the 46 topics' names.
How can I show topics of reuters dataset in Keras?
https://keras.io/datasets/#reuters-newswire-topics-classification
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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.
The Reuters-21578 dataset is a collection of documents with news articles. The original corpus has 10,369 documents and a vocabulary of 29,930 words. Source: Topic Model Based Multi-Label Classification from the Crowd.
Associated mapping of topic labels as per original Reuters Dataset with the topic indexes in Keras version is:
['cocoa','grain','veg-oil','earn','acq','wheat','copper','housing','money-supply',
'coffee','sugar','trade','reserves','ship','cotton','carcass','crude','nat-gas',
'cpi','money-fx','interest','gnp','meal-feed','alum','oilseed','gold','tin',
'strategic-metal','livestock','retail','ipi','iron-steel','rubber','heat','jobs',
'lei','bop','zinc','orange','pet-chem','dlr','gas','silver','wpi','hog','lead']
To understand the approach of extracting the above mapping, please follow this thread comment.
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