|
|
@ -188,10 +188,11 @@ Amazing🤩! For some of the features, there's a noticeable difference in the di
|
|
|
|
palette <- c(ORANGE = "orange", WHITE = "wheat")
|
|
|
|
palette <- c(ORANGE = "orange", WHITE = "wheat")
|
|
|
|
|
|
|
|
|
|
|
|
# We need the encoded Item Size column to use it as the x-axis values in the plot
|
|
|
|
# We need the encoded Item Size column to use it as the x-axis values in the plot
|
|
|
|
pumpkins_select$item_size <- baked_pumpkins$item_size
|
|
|
|
pumpkins_select_plot<-pumpkins_select
|
|
|
|
|
|
|
|
pumpkins_select_plot$item_size <- baked_pumpkins$item_size
|
|
|
|
|
|
|
|
|
|
|
|
# Create the grouped box plot
|
|
|
|
# Create the grouped box plot
|
|
|
|
ggplot(pumpkins_select, aes(x = `item_size`, y = color, fill = color)) +
|
|
|
|
ggplot(pumpkins_select_plot, aes(x = `item_size`, y = color, fill = color)) +
|
|
|
|
geom_boxplot() +
|
|
|
|
geom_boxplot() +
|
|
|
|
facet_grid(variety ~ ., scales = "free_x") +
|
|
|
|
facet_grid(variety ~ ., scales = "free_x") +
|
|
|
|
scale_fill_manual(values = palette) +
|
|
|
|
scale_fill_manual(values = palette) +
|
|
|
@ -296,6 +297,7 @@ wf_fit <- log_reg_wf %>%
|
|
|
|
# Print the trained workflow
|
|
|
|
# Print the trained workflow
|
|
|
|
wf_fit
|
|
|
|
wf_fit
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
```
|
|
|
|
```
|
|
|
|
|
|
|
|
|
|
|
|
The model print out shows the coefficients learned during training.
|
|
|
|
The model print out shows the coefficients learned during training.
|
|
|
|