recipes
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Pipeable steps for feature engineering and data preprocessing to prepare for modeling
For cases like [this one](https://stackoverflow.com/questions/76158409/log-transform-outcome-variable-in-tidymodels-workflow), we should: - supplement this error message with "you should do this with the outcome data" - point to a FAQ or something that we...
I'm finding `step_bagimpute` not particularly scalable for large datasets. This is not ideal given that bagged imputations are supposed to be the scalable alternative to imputing via KNN. To illustrate,...
Currently it requires that the input tibble is appropriately sorted, but we could just pass a column to sort by to `dplyr::lag` in the implementation. Probably can get around to...
The same dataset with an NA value does not work with caret-recipes pipeline whereas the single caret does not cause any issues. ``` r library(caret) #> Loading required package: lattice...
Hey everyone, just spent a couple hours debugging an issue where `prep()` was quietly replacing missing factor levels with `NA` in a variable that ultimately wasn't included in any preprocessing...
If you specify a `recipe()` with a particular data frame, then `prep()` with a different data frame, `check_training_data()` does a few checks to make sure the two are compatible. In...
Should there be a catch for this particular error that gets produced in `step_dummy()` when it tries to calculate too big of a matrix? I realise this will eventually get...
A surprising error on `step_select`. If you deselect a predictor using `step_select`, then fit a model with the recipe and try to predict, it will yield an error message ```...
## The problem I'm having trouble with fitting a cubic spline with fixed knots. I would expect the number of terms in the fitted model to be equal to `degree...
I think it would make a lot of sense to add a "type" argument to this step with the options of "centered" & "lagging". Ideally, I would really like to...