mc_pr_plot: Produce a precision-recall plot for a set of predicted...

In gweissman/gmish: Miscellaneous Functions for Predictive Modeling

Produce a precision-recall plot for a set of predicted probabilities for a single model across multiple classes.

Description

Produce a precision-recall plot for a set of predicted probabilities for a single model across multiple classes.

Usage

mc_pr_plot(form, data, max_intervals = 1000)

Arguments

form	A formula where the left-hand side is the set variable representing the observed outcomes for each class, 0 or 1. The right-hand side represents the column names of the different class probabilities. The names of the columns don't matter to the model, but the order of the observed (on the left) and predicted (on the right) should align.
data	A data frame that contains one observed and one predicted column for each class.
max_intervals	The maximum number of thresholds to evaluate. Default = 1000.

Examples

library(ranger)
library(palmerpenguins)
pp <- penguins[complete.cases(penguins),]
m1 <- ranger(species ~ island + bill_length_mm + flipper_length_mm + body_mass_g + sex,
      data = pp, probability = TRUE)
p_obj <- predict(m1, data = pp)
results <- data.frame(p_obj$predictions, ohe(pp$species, drop_ref = FALSE))
mc_pr_plot(pp.species_Adelie + pp.species_Chinstrap + pp.species_Gentoo ~
      Adelie + Chinstrap + Gentoo,
      data = results)

gweissman/gmish documentation built on Feb. 21, 2025, 1:20 a.m.