consistency unknown legend cls1 bughunt

source/classification1.Rmd

@@ -324,7 +324,7 @@ Figure \@ref(fig:05-knn-1).
 perim_concav_with_new_point <-  bind_rows(cancer,
                                           tibble(Perimeter = new_point[1],
                                                  Concavity = new_point[2],
-                                                 Class = "unknown")) |>
+                                                 Class = "Unknown")) |>
   ggplot(aes(x = Perimeter,
              y = Concavity,
              color = Class,
@@ -379,7 +379,7 @@ not, if you consider the other nearby points.
 perim_concav_with_new_point2 <- bind_rows(cancer,
                                           tibble(Perimeter = new_point[1],
                                                  Concavity = new_point[2],
-                                                 Class = "unknown")) |>
+                                                 Class = "Unknown")) |>
   ggplot(aes(x = Perimeter,
              y = Concavity,
              color = Class,
@@ -466,7 +466,7 @@ In order to find the $K=5$ nearest neighbors, we will use the `slice_min` functi
 perim_concav <- bind_rows(cancer,
                           tibble(Perimeter = new_point[1],
                                  Concavity = new_point[2],
-                                 Class = "unknown")) |>
+                                 Class = "Unknown")) |>
   ggplot(aes(x = Perimeter,
              y = Concavity,
              color = Class,
@@ -950,7 +950,7 @@ whether you need to standardize your data.
 attrs <- c("Area", "Smoothness")
 
 # create a new obs and get its NNs
-new_obs <- tibble(Area = 400, Smoothness = 0.135, Class = "unknown")
+new_obs <- tibble(Area = 400, Smoothness = 0.135, Class = "Unknown")
 my_distances <- table_with_distances(unscaled_cancer[, attrs],
                                      new_obs[, attrs])
 neighbors <- unscaled_cancer[order(my_distances$Distance), ]
@@ -989,7 +989,7 @@ unscaled <- ggplot(unscaled_cancer, aes(x = Area,
   ), color = "black", linewidth = 0.5, show.legend = FALSE)
 
 # create new scaled obs and get NNs
-new_obs_scaled <- tibble(Area = -0.72, Smoothness = 2.8, Class = "unknown")
+new_obs_scaled <- tibble(Area = -0.72, Smoothness = 2.8, Class = "Unknown")
 my_distances_scaled <- table_with_distances(scaled_cancer[, attrs],
                                             new_obs_scaled[, attrs])
 neighbors_scaled <- scaled_cancer[order(my_distances_scaled$Distance), ]
@@ -1141,7 +1141,7 @@ neighbors <- rare_cancer[order(my_distances$Distance), ]
 rare_plot <- bind_rows(rare_cancer,
                        tibble(Perimeter = new_point[1],
                               Concavity = new_point[2],
-                              Class = "unknown")) |>
+                              Class = "Unknown")) |>
   ggplot(aes(x = Perimeter, y = Concavity, color = Class, shape = Class)) +
   geom_point(alpha = 0.5) +
   labs(color = "Diagnosis",