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Transformer on a forecast problem [D]

Reddit r/MachineLearning / 3/16/2026

💬 OpinionIdeas & Deep AnalysisTools & Practical UsageModels & Research
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Key Points

  • The author is attempting to forecast availability for the next four days, framing it as a time-series classification problem with a target state like 'busy'.
  • The current feature set includes day and time encodings (sin/cos) plus a signal from the item being forecasted.
  • They are experimenting with a Transformer model for forecasting and have tried mixing class weights to address class imbalance.
  • They are seeking ideas and feedback on modeling approaches to improve forecast accuracy, indicating this is an informal request for practical guidance.

Hello Everyone. I’m posting here to look for any ideas for my current problem. I’m trying to predict if something will be available or not in the next 4 days. As expected the normal load of that thing is during the day. My current model is just predicting the state “busy” for that period of time where there is multiple loads during the day. Right now I have 8 features for day and time(sin and cos) and the signal from the thing.

I’ve mixed the weights on the classes but couldn’t get what I wanted

submitted by /u/SomePiece7833
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