Package :: PYPI :: tsts

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Fixed a minor bug

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I added 2 new args X\_valid and y\_valid to TimeSeriesForester class to specify validation dataset explicitly.

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  • Fixed bias bug on predict method
  • Fixed localscaler bug (wrong dimension)
  • Added random dataset sample feature
  • Updated SCINet
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Added SCINet and the results

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  • Added new tutorial
  • Added new optimizers: AdamW and SAM
  • Added new local scaler: HistricalInertia
  • Added new losses: MAE and SmoothMAE
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  • Deleted ADD\_LAST\_STEP\_VAL which is replaced by local scalers now
  • Built docs
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Following local scaler modules are added

  • NOOP: Do nothing
  • LastStep: Adding last step value
  • AutoRegressiveModel: Adding output of AR model
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  • Refactored Solver class
  • Refactored TimeSeriesForecaster class
  • Changed default config values
  • Added new default config values
  • Added new results
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  • Added Informer
  • Added MAE and MSE metrics
  • Updated README
  • Added StepScheduler
  • Added new result
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  • Fixed a minor bug which occurs when using gpu Since I found bias added is not moved to gpu, I added lines like bias.to(device).
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  • Fixed predict bug Fixed a bug that bias is used wrongly.
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  • Fixed ADD\_LAST\_STEP\_VAL Before, ADD\_LAST\_STEP\_VAL can be set to True only when input/output features are the same. We fixed ADD\_LAST\_STEP\_VAL can be set to True even if …

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Changed to initialize X\_scaler and y\_scaler separately Expanded ADD\_LAST\_STEP\_VAL to output each feature Fixed Seq2Seq to work on multiple output features

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  • Added schedulers
  • Added deterministic results
  • Fixed Seq2Seq
  • Updated NBeats result
  • Added Seq2Seq result
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Fixed StandardScaler dimension bug Modified Seq2Seq (added a new layer to regressor and bias terms) Added TrendBlock to NBeats

  • Fixed minor bugs
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Fixed a minor bug of predict method

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tsts

toolset for time series forecasting

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