fixed fig whitespace for classification1

Author: ttimbers

classification1.Rmd

@@ -455,7 +455,7 @@ You will see in the `mutate` \index{mutate} step below, we compute the straight-
 distance using the formula above: we square the differences between the two observations' perimeter 
 and concavity coordinates, add the squared differences, and then take the square root.
 
-```{r 05-multiknn-1, echo = FALSE, fig.height = 3.5, fig.width = 4.5, fig.cap="Scatter plot of concavity versus perimeter with new observation represented as a red diamond."}
+```{r 05-multiknn-1, echo = FALSE, fig.height = 3.5, fig.width = 4.5, fig.pos = "H", out.extra="", fig.cap="Scatter plot of concavity versus perimeter with new observation represented as a red diamond."}
 perim_concav <- bind_rows(cancer, 
                           tibble(Perimeter = new_point[1], 
                                  Concavity = new_point[2], 
@@ -1255,7 +1255,7 @@ classifier would make. We can see that the decision is more reasonable; when the
 to those labeled malignant, the classifier predicts a malignant tumor, and vice versa when they are 
 closer to the benign tumor observations.
 
-```{r 05-upsample-plot, echo = FALSE, fig.height = 3.5, fig.width = 4.5, fig.cap = "Upsampled data with background color indicating the decision of the classifier."}
+```{r 05-upsample-plot, echo = FALSE, fig.height = 3.5, fig.width = 4.5, fig.pos = "H", out.extra="", fig.cap = "Upsampled data with background color indicating the decision of the classifier."}
 knn_spec <- nearest_neighbor(weight_func = "rectangular", neighbors = 7) |>
   set_engine("kknn") |>
   set_mode("classification")