added points to predsel subsec cls2 bughunt

source/classification2.Rmd

@@ -1400,6 +1400,7 @@ res <- tibble(ks = ks, accs = accs, fixedaccs = fixedaccs, nghbrs = nghbrs)
 
 plt_irrelevant_accuracies <- ggplot(res) +
               geom_line(mapping = aes(x=ks, y=accs)) +
+  	      geom_point(mapping = aes(x=ks, y=accs)) +
               labs(x = "Number of Irrelevant Predictors",
                    y = "Model Accuracy Estimate") +
   theme(text = element_text(size = 18), axis.title=element_text(size=18))
@@ -1420,6 +1421,7 @@ this evidence; if we fix the number of neighbors to $K=3$, the accuracy falls of
 
 ```{r 06-neighbors-irrelevant-features, echo = FALSE, warning = FALSE, fig.retina = 2, out.width = "65%", fig.align = "center", fig.cap = "Tuned number of neighbors for varying number of irrelevant predictors."}
 plt_irrelevant_nghbrs <- ggplot(res) +
+              geom_point(mapping = aes(x=ks, y=nghbrs)) +
               geom_line(mapping = aes(x=ks, y=nghbrs)) +
               labs(x = "Number of Irrelevant Predictors",
                    y = "Tuned number of neighbors") +
@@ -1434,6 +1436,7 @@ res_tmp <- res %>% pivot_longer(cols=c("accs", "fixedaccs"),
                                 values_to="accuracy")
 
 plt_irrelevant_nghbrs <- ggplot(res_tmp) +
+              geom_point(mapping = aes(x=ks, y=accuracy, color=Type)) +
               geom_line(mapping = aes(x=ks, y=accuracy, color=Type)) +
               labs(x = "Number of Irrelevant Predictors", y = "Accuracy") +
               scale_color_manual(labels= c("Tuned K", "K = 3"), values = c("darkorange", "steelblue")) +
@@ -1661,6 +1664,7 @@ where the elbow occurs, and whether adding a variable provides a meaningful incr
 
 fwd_sel_accuracies_plot <- accuracies |>
   ggplot(aes(x = size, y = accuracy)) +
+  geom_point() +
   geom_line() +
   labs(x = "Number of Predictors", y = "Estimated Accuracy")  +
   theme(text = element_text(size = 20), axis.title=element_text(size=20))