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Unified API : `model.params` attribute

See original GitHub issue

Hello! Firstly, I wanted to thank you for this wonderful library.

Unified API to get model’s params might make darts more convenient. For example, to get params of Exponential Smoothing model, We have to code like this:

model = ExponentialSmoothing()
model.fit(train)

print(model.model.model.params) # {'smoothing_level': 0.5789473661331209, 'smoothing_slope': ...

So, I want to implement ~~model.get_params() method like sklearn.~~ model.params attribute with property like statsmodels and fbprophet.

I would like to get your opinion before send PR. Thanks!

Models
- abstract params() function in the ForecastingModel superclass
- ARIMA
- AutoARIMA
- Baseline Models
  - NaiveDrift
  - NaiveMean
  - NaiveSeasonal
- ExponentialSmoothing
- FFT
- Prophet
- StandardRegressionModel
- TCNModel
- Theta
- TorchForecastingModel (RNNModel)
Preprocessing
- Scaler wrapper

Issue Analytics

State:
Created 3 years ago
Reactions:1
Comments:8 (3 by maintainers)

Top GitHub Comments

2reactions

hrzncommented, Sep 29, 2020

+1 for that, it’s a good idea

2reactions

LeoTafticommented, Sep 29, 2020

Hello @norihitoishida, thanks for your suggestion and offering to help! I think that would be a nice addition to our library.

Make sure to check out our guidelines first and to include a couple unit tests. Thanks!

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