I’m testing the tidymodels package to do some modeling.

So far I started with the basic workflow (recipe + spec), no cross-validation.

Here you have a repex for a sample dataframe, with one endpoint column (factor of 0 and 1), and 20 descriptor variables (genes, numeric variables).

For this I want to perform an SVM with a radial kernel for all the genes predicting the endpoint. The formula would be `endpoint ~ ., data = data`

However, I’m getting the following error:

```
> svm_fit <- fit(svm_wflow, data)
Error in eval_tidy(env$formula[[2]], env$data) : object '.' not found
```

Apparently is not recognizing the `. `

in the formula, but not sure why, nor how to fix it.

```
library(tidymodels)
tidymodels_prefer()
# Create the endpoint variable
endpoint <- factor(rep(c(1, 0), each = 10))
# Create the gene columns
genes <- data.frame(matrix(rnorm(20 * 20), ncol = 20))
# Combine the endpoint and gene columns into a dataframe
data <- data.frame(endpoint, genes)
# Recipe
svm_linear_rec <-
recipe(endpoint ~ ., data = data) %>%
step_normalize(all_numeric_predictors()) %>%
step_dummy(endpoint)
# Spec
svm_spec <-
svm_rbf(cost = tune(), rbf_sigma = tune()) %>%
set_engine("kernlab") %>%
set_mode("classification")
# Workflow
svm_wflow <-
workflow() %>%
add_model(svm_spec) %>%
add_recipe(svm_linear_rec)
# Fit model
svm_fit <- fit(svm_wflow, data)
```