plot doesn't work

R/predictions.R

@@ -274,7 +274,7 @@ predictions <- function(model,
 
     # if type is NULL, we backtransform if relevant
     type_string <- sanitize_type(model = model, type = type, calling_function = "predictions")
-    if (type_string == "invlink(link)") {
+    if (identical(type_string, "invlink(link)")) {
         if (is.null(hypothesis)) {
             type_call <- "link"
         } else {

R/sanitize_condition.R

@@ -57,6 +57,7 @@ sanitize_condition <- function(model, condition, variables = NULL, modeldata = N
     respname <- insight::find_response(model)
 
     flag <-  checkmate::check_true(all(names(condition) %in% c(colnames(dat), "group")))
+    browser()
     if (!isTRUE(flag)) {
         msg <- sprintf("Entries in the `condition` argument must be element of: %s",
                        paste(colnames(dat), collapse = ", "))

book/articles/machine_learning.qmd

@@ -88,11 +88,19 @@ mod <- linear_reg(mode = "regression") |>
 avg_comparisons(mod, newdata = bikes, type = "response")
 ```
 
+We can also plot the results as usual:
+
+```{r, warning = FALSE}
+plot_predictions(mod, condition = "temp", points = .2)
+```
+
 When the engine is not supported by `marginaleffects`, we can also obtain correct results, but no uncertainy estimates. Here is a random forest model:
 
 ```{r}
 forest_tidy <- rand_forest(mode = "regression") |>
     set_engine("ranger") |>
     fit(count ~ ., data = bikes)
 avg_comparisons(forest_tidy, newdata = bikes, type = "numeric")
+
+plot_predictions(forest_tidy, newdata = bikes, by = "temp", type = "numeric")
 ```