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tidymodels
Pipeable steps for feature engineering and data preprocessing to prepare for modeling
Part of https://github.com/tidymodels/planning/issues/29 VERY WIP
It would be really cool if `recipes` could support missing variable imputation with the `missForest` package Good example here: https://rpubs.com/lmorgan95/MissForest#:~:text=MissForest%20is%20a%20random%20forest,then%20predicts%20the%20missing%20part. On another note, I'm wondering if there would be value...
```suggestion ``` _Originally posted by @simonpcouch in https://github.com/tidymodels/recipes/pull/1255#discussion_r1392823074_
``` r library(tidymodels) recipe(mpg ~ ., data = mtcars) %>% step_interact(terms = starts_with("dis")) %>% prep() %>% bake(new_data = NULL) #> Error in `step_interact()`: #> Caused by error: #> ! `starts_with()`...
the documentation states that you can read more about how prefix works, but doesn't have any information
Possible bug as the `options` argument is not returning the same output as `splines::ns`. I'd like to specify a spline for a continuous variable using `step_ns`. The docs say I...
Related to [tidymodels/tune#660](https://github.com/tidymodels/tune/issues/660#issuecomment-2035486249). It looks like, currently, `tune_args()` doesn't include arguments marked for tuning if they're not tunable. ``` r library(tidymodels) rec % step_impute_bag( Status, Home, Marital, Job, Income, Assets,...
Hi, `step_corr()` can remove highly correlated continuous variables using Pearson or Spearman correlation analysis. However, prefilter functions for categorical variables were not provided in the `recipes` package. I have 20...
We are very interested in using an autoencoder to reduce the dimension to input into a machine-learning model. We found this issue: https://github.com/tidymodels/recipes/issues/35. Did it mean that the autoencoder function...
Bug first discovered in https://github.com/tidymodels/recipes/issues/1290. - [ ] add tests - [ ] add news # Before ``` r library(recipes) ex_data [1] a c #> Levels: a c rec_res prep()...
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Pipeable steps for feature engineering and data preprocessing to prepare for modeling