Example of brms model for fitting Bayesian (Stan) categorical model in R

brms_categorical.R

library(brms)
library(tidyverse)
library(caret)

rstan_options(auto_write=TRUE)
options(mc.cores=parallel::detectCores ()) # Run on multiple cores
set.seed(3875)

ir <- data.frame (scale (iris[, -5]), Species=iris[, 5])
system.time (b2 <- brm (Species ~ Petal.Length + Petal.Width + Sepal.Length + Sepal.Width,
                        data=ir, family="categorical", 
                        prior=c(set_prior("normal (0, 8)"))))

pred <- predict(b2)
pred2 <- as.data.frame(pred) %>% 
  mutate(actual = as.character(ir$Species),
         pred   = colnames(pred)[max.col(pred,ties.method="first")],
         pred   = str_remove(pred,"P\\(Y = "),
         pred   = str_remove(pred,"\\)"),
         actual = factor(actual),
         pred   = factor(pred))

confusionMatrix(pred2$pred, pred2$actual)