ROC Curves with dplyr

require(tidyverse)

Loading required package: tidyverse
Loading tidyverse: ggplot2
Loading tidyverse: tibble
Loading tidyverse: tidyr
Loading tidyverse: readr
Loading tidyverse: purrr
Loading tidyverse: dplyr
Conflicts with tidy packages -----------------------------------
filter(): dplyr, stats
lag():    dplyr, stats

roc <- iris %>% 
  gather(Metric, Value, -Species) %>% 
  mutate(Positive = Species == "virginica") %>% 
  group_by(Metric, Value) %>% 
  summarise(Positive = sum(Positive), 
            Negative = n() - sum(Positive)) %>% 
  arrange(-Value) %>% 
  mutate(TPR = cumsum(Positive) / sum(Positive), 
         FPR = cumsum(Negative) / sum(Negative))

roc %>% 
  group_by(Metric) %>% 
  summarise(AUC = sum(diff(FPR) + na.omit(lead(TPR) + TPR)) / 2)

roc %>% 
  ggplot(aes( x= FPR, y = TPR, color = Metric)) +
  geom_line() +
  geom_abline(lty = 2) +
  xlab("False positive rate (1-specificity)") + 
  ylab("True positive rate (sensitivity)") +
  ggtitle("ROC at predicting Virginica iris species")