Carl Goodwin
Carl Goodwin
Hi - this code worked okay with the prior version (0.5.10): ``` r library(tidyquant) #> Loading required package: lubridate #> #> Attaching package: 'lubridate' #> The following object is masked...
The dev version of dtplyr with `complete` throws an error when `nesting`. ``` r library(tidyverse) library(dtplyr) data_df % complete(nesting(group), date = "2021-01-01") #> # A tibble: 4 x 3 #>...
When `fct_relevel` is used after `reorder_within`, it would be useful if there were a way to generalise positioning a lumped grouping. In the example below, it would mean replacing the...
I'd like to use `none is.na` with `across` rather than `all !is.na`, but it's relatively expensive when applied to a large number of rows and columns. ``` r library(tidyverse) library(microbenchmark)...
Should it be possible to switch `percent()` for `label_percent()` inside `geom_label()` per the examples below? ``` r library(tidyverse) library(scales, warn.conflicts = FALSE) tribble(~name, ~pct, "A", 0.1, "B", 0.2) |> ggplot(aes(name,...
Reprex: ``` r library(tabnet) library(tidymodels) library(modeldata) data("lending_club", package = "modeldata") rec recipe() |> update_role(Class, new_role = "outcome") |> update_role(-has_role("outcome"), new_role = "predictor") re_run [Epoch 001] Loss: 147.732330 #> [Epoch 002]...
Running the example below in a fresh R session, `tabnet_pretrain()` works with `device = "mps"`, but `tabnet_fit()` hangs (no message) and I need to Terminate R to recover. Session info...
aorsf is a great addition to bonsai! Any chance of supporting `mtry_prop`? ``` r library(tidymodels) library(bonsai) set.seed(1) folds set_mode("regression") lgbm_wflow add_model(mod_lgbm) |> add_recipe(rec) aorsf_wflow add_model(mod_aorsf) |> add_recipe(rec) # lightgbm supports...
Simon hi - I wanted to label `autoplot("weights")` with the names of the engines. Use of `stacks:::top_coefs()` was very handy for getting the names! I was curious though why the...
Hi - Stacks is proving very effective at improving model performance for me (using the output from `finetune::tune_sim_anneal()`). Thank you! I am occasionally running into this problem though stacking classification...