library(randomForest)
library(ggplot2)
library(randomForestExplainer)

n <- 100
p <- 4

# Create data:
xrandom <- matrix(rnorm(n*p)+5, nrow=n)
colnames(xrandom)<- paste0("x",2:5)
d <- data.frame(xrandom)
d$x1 <- factor(sample(1:2, n, replace=T))

# Equation:
y <- d$x2 + rnorm(n)/5

y[d$x1==1] <- y[d$x1==1]+5
d$y <- y

# Random Forest:
fr <- randomForest(y ~ ., data=d,localImp=T)

# Random Forest Explainer:
interactions_frame <- min_depth_interactions(fr, names(d)[-6])
head(interactions_frame, 2)

variable    root_variable mean_min_depth occurrences interaction
1       x1            x1       4.670732           0       x1:x1
2       x1            x2       2.606190         221       x2:x1
  uncond_mean_min_depth
1              1.703252
2              1.703252