protect(): protection stack overflow in Ranger

Published by onesixx on 19-05-0819-05-08

https://github.com/imbs-hl/ranger/issues/103

due to the formula interface

rfModel <- ranger(Species~. , data = iris, mtry = 2, num.trees = 1000, importance = “impurity”, probability = T)

rfModel <- ranger(dependent.variable.name = “Species”, data = iris, mtry = 2, num.trees = 1000, importance = “impurity”, probability = T)

`importance_pvalues()` function

library(ranger)

num.permutations <- 100

# Run RF
rf <- ranger(dependent.variable.name = "Species", data = iris, importance = "permutation")

# Permute and compute importance again (be sure to use same parameters as above)
vimp <- replicate(num.permutations, {
  dat <- iris
  dat[, "Species"] <- dat[sample(nrow(dat)), "Species"]
  ranger(dependent.variable.name = "Species", data = dat, importance = "permutation")$variable.importance
})

# Compute p-values
pval <- sapply(1:nrow(vimp), function(i) {
  (sum(vimp[i, ] >= rf$variable.importance[i]) + 1)/(ncol(vimp) + 1)
})

res <- cbind(rf$variable.importance, pval)
colnames(res) <- c("importance", "pvalue")

res

protect(): protection stack overflow in Ranger

due to the formula interface

`importance_pvalues()` function

onesixx

R Analysis

네트워크 분석

R Analysis

Optimization Objectives

R Analysis

xgBoost :: classification example

protect(): protection stack overflow in Ranger

due to the formula interface

importance_pvalues() function

onesixx

Related Posts

R Analysis

네트워크 분석

R Analysis

Optimization Objectives

R Analysis

xgBoost :: classification example

`importance_pvalues()` function