business-science / modeltime

Modeltime unlocks time series forecast models and machine learning in one framework
https://business-science.github.io/modeltime/
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updates for upcoming parsnip #8

Closed topepo closed 4 years ago

topepo commented 4 years ago

I'll be sending parsnip 0.1.2 to CRAN very soon and it has some differences in how to choose encodings from how modeltime currently does it.

Using arima_reg as an example, the model definition should use the new set_encoding() interface (rather than passing indicators directly). To make sure that parsnip (and, soon workflows) does no modifications to the predictors columns, use

set_encoding(
  model = "arima_reg",
  eng = "auto_arima",
  mode = "regression",
  options = list(
    predictor_indicators = "none",
    compute_intercept = FALSE,
    remove_intercept = FALSE
  )
)

They same type of declaration is required for each engine/model combination.

The current GH version of parsnip can be used for testing.

mdancho84 commented 4 years ago

Thanks Max. I'm on it. I'll work on the updates.

mdancho84 commented 4 years ago

@topepo I've updated. 2 minor issues in case you get this from others:

image

topepo commented 4 years ago

New parsnip was accepted to CRAN

mdancho84 commented 4 years ago

Nice work. Will send modeltime 0.0.2 to CRAN shortly.

mdancho84 commented 4 years ago

Modeltime 0.0.2 is on CRAN, which incorporates parsnip 0.1.2. We are good to go.