Comments (4)
DavisVaughan
commented on July 22, 2024
We now always return a data frame from the formula method when preparing and preprocessing.
04e400f
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DavisVaughan
commented on July 22, 2024
We don't need an arg for the outcome type because we consistently return a tibble from all methods
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DavisVaughan
commented on July 22, 2024
prepare() currently still returns y as whatever went in. We could use standardize() first. This would match with recipes / formula interface.
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github-actions
commented on July 22, 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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Related Issues (20)
- forge fails with non-standard roles HOT 4
- Release hardhat 1.0.0 HOT 1
- Error in out$extras$final(predictors_extras, outcomes_extras): argument "outcomes_extras" is missing, with no default HOT 15
- Release hardhat 1.1.0 HOT 2
- get_outcome_levels blueprint method? HOT 5
- Post recipes 1.0.0 upkeep HOT 1
- Release hardhat 1.2.0 HOT 1
- Pass through strings_as_factors arg HOT 3
- Problem with predicting on new data for character column HOT 5
- Problem with a formula with spaces in the name of a factor and indicators = "none" HOT 2
- `mold()` inconsistently preserves (with XY method) or ignores (with formula method) non-base vector classes HOT 2
- Do a pass over `validate_is()` with an eye towards performance HOT 1
- Avoid `as_tibble()` where possible HOT 2
- multi-outcomes support for `spruce_prob_multi` shall clarify input format for multiple `pred_levels` HOT 2
- Upkeep for hardhat HOT 1
- Regression in development version of hardhat when using sf objects HOT 3
- Release hardhat 1.3.0 HOT 1
- Dynamically calculate weights HOT 5
- Using a division on the left-hand side of a formula throws an "Interaction terms can't be specified on the LHS of `formula`" HOT 2
- importance weights not compatible with DALEXtra::model_profile HOT 2
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