CODEWITHSUNDEEP
pythondatetimemachine-learningtime-serieslstm
Saad el harchi
Saad el harchi

Reputation: 59

How to train a LSTM on a sequence of dates?

if i wanted to train an lstm to predict the next date in a sequence of dates, how would i do that since lstm require a scaled value?

example of data:

date next date
2012-05-12 2012-05-13
2012-05-13 2012-05-19
2012-05-19 2012-05-20
2012-05-20 2012-05-22
2012-05-22 2012-05-26
2012-05-26 2012-05-27
2012-05-27 2012-05-30
2012-05-30 2012-06-12
2012-06-12 2012-05-19
2012-06-19 2012-06-25

Upvotes: 2

Views: 1069

Answers (1)

mrk
mrk

Reputation: 10406

You could hand over the date split into three inputs: One would then be the year, the other the month, and the last the day. While normalizing your inputs definitely makes sense, however I would not entirely agree with your "LSTM requires".

Day and month are already limited to a range of values which can be scaled

  • day (1 - 31)
  • month (1 - 12)

For year you need to make an educated assumption based on your application. So that year can then also be transferred to a scaled value. Judging from your data, it might be that year is constant at 2012 and it is not needed to begin with.

  • year (2012 - 2013(?))

Note: Ask yourself whether you give the neural network enough system information to be able to predict the next date - meaning, is there already enough of a pattern in your data? Otherwise you might end up training a random predictor.

Upvotes: 2

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