avoid [link] parsing

Author: dsweber2

R/arx_classifier.R

@@ -34,14 +34,14 @@
 #' ```
 #'
 #' The key takeaway from the predictions is that there are two prediction
-#'   classes: (-Inf, 0.25] and (0.25, Inf). This is because for our goal of
+#'   classes: `(-Inf, 0.25]` and `(0.25, Inf)`. This is because for our goal of
 #'   classification the classes must be discrete. The discretization of the
 #'   real-valued outcome is controlled by the `breaks` argument, which defaults
-#'   to 0.25. Such breaks will be automatically extended to cover the entire
-#'   real line. For example, the default break of 0.25 is silently extended to
-#'   breaks = c(-Inf, .25, Inf) and, therefore, results in two classes: [-Inf,
-#'   0.25] and (0.25, Inf). These two classes are used to discretize the
-#'   outcome. The conversion of the outcome to such classes is handled
+#'   to `0.25`. Such breaks will be automatically extended to cover the entire
+#'   real line. For example, the default break of `0.25` is silently extended to
+#'   `breaks = c(-Inf, .25, Inf)` and, therefore, results in two classes:
+#'   `[-Inf, 0.25]` and `(0.25, Inf)`. These two classes are used to discretize
+#'   the outcome. The conversion of the outcome to such classes is handled
 #'   internally. So if discrete classes already exist for the outcome in the
 #'   `epi_df`, then we recommend to code a classifier from scratch using the
 #'   `epi_workflow` framework for more control.