Matching topic labels according to the original Reuters dataset with topic indexes in the Keras version:
['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, follow this comment on the topic .