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