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Comments (5)

jonthegeek avatar jonthegeek commented on June 29, 2024 1

I'll go ahead and close this issue, since this isn't the right solution. Thanks for the feedback!

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DavisVaughan avatar DavisVaughan commented on June 29, 2024

It is probably better to just store the levels in the fit object.

If you are following the model template then right here you have access to the outcomes, so just pluck off the levels and store then in the model result

{{model}}_bridge <- function(processed, ...) {
predictors <- processed$predictors
outcome <- processed$outcomes[[1]]
fit <- {{model}}_impl(predictors, outcome)
new_{{model}}(
coefs = fit$coefs,
blueprint = processed$blueprint
)
}

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DavisVaughan avatar DavisVaughan commented on June 29, 2024

get_outcome_levels() could be used on processed$outcomes if you want, but it takes into account the fact that you might have multiple outcome columns, which is why it returns a list of factor levels.

It is probably simpler for you to just call levels(outcome) there and store that.

I don't think modifying get_outcome_levels() is the right solution

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jonthegeek avatar jonthegeek commented on June 29, 2024

Oooh, storing them in the model object is a good option!

I definitely wasn't confident this was the right solution, but it wasn't clear what was. Perhaps a classification vignette would help?

FWIW, tabnet extracts them from the blueprint, which is what led me to that solution.

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github-actions avatar github-actions commented on June 29, 2024

This issue has been automatically locked. If you believe you have found a related problem, please file a new issue (with a reprex: https://reprex.tidyverse.org) and link to this issue.

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