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In many papers and articles related to Recurrent Neural networks(RNN) with specific (LSTM)Long short term memory technique I have seen that in training phase labels and ground truth data are fed with the input data.Whereas In most of the classification techique only the labels are required with the data in the training phase.

Please help me understand why we need both labels and ground truth in training phase.

Reference LSTM Paper

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In that context, ground truth and gold labels are synonymous. LSTMs don't require any additional supervision compared to other supervised machine learning models.

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  • $\begingroup$ But I have seen that in LSTM programming codes they maintain dictionary of labels? $\endgroup$ – 李 慕 Aug 1 '16 at 5:37
  • $\begingroup$ @NaseerAhmed They often maintain a dictionary mapping word to word index, maybe this is what you read. $\endgroup$ – Franck Dernoncourt Aug 1 '16 at 14:35

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