## ----include = FALSE----------------------------------------------------------
knitr::opts_chunk$set(collapse = TRUE, comment = "#>")

## -----------------------------------------------------------------------------
library(rankimp)

judges <- rbind(
  permutation_seed1 = c(1, 2, 3, 4),
  permutation_seed2 = c(1, 2, 3, 4),
  shap              = c(1, 3, 2, 4),
  impurity          = c(2, 1, 3, 4)
)
colnames(judges) <- c("income", "age", "balance", "region")

consensus_rank(judges)

## -----------------------------------------------------------------------------
importance <- rbind(
  permutation = c(income = 0.31, age = 0.12, balance = 0.12, region = 0.03),
  impurity    = c(income = 0.44, age = 0.20, balance = 0.05, region = 0.02)
)

importance_to_rank(importance)

## ----eval = requireNamespace("randomForest", quietly = TRUE)------------------
set.seed(1)
fit <- randomForest::randomForest(mpg ~ ., data = mtcars, ntree = 200)

J <- importance_judges(
  fit,
  methods = c("permutation", "mdi"),
  data    = mtcars,
  target  = "mpg"
)
J

consensus_rank(J)$ranking

## -----------------------------------------------------------------------------
tied <- rbind(
  c(1, 1, 3, 4),
  c(1, 1, 3, 4),
  c(2, 1, 3, 4)
)
colnames(tied) <- c("income", "age", "balance", "region")

consensus_rank(tied)$ranking

## -----------------------------------------------------------------------------
consensus_rank(judges, weights = c(1, 1, 1, 0.5))$ranking