distanceRandomForest: Distance calculation based on RandomForest Proximity or Depth

In CaseBasedReasoning: Case Based Reasoning

Distance calculation based on RandomForest Proximity or Depth

Description

Distance calculation based on RandomForest Proximity or Depth

Usage

distanceRandomForest(
  x,
  y = NULL,
  rfObject,
  method = "Proximity",
  threads = NULL
)

Arguments

x	a data.frame
y	a second data.frame
rfObject	ranger object
method	distance calculation method, Proximity (Default) or Depth.
threads	number of threads to use

Value

a dist or a matrix object with pairwise distance of observations in x vs y (if not null)

Examples

library(ranger)
# proximity pairwise distances
rf.fit <- ranger(Species ~ ., data = iris, num.trees = 500, write.forest = TRUE)
distanceRandomForest(x = iris[, -5], rfObject = rf.fit, method = "Proximity", threads = 1)

# depth distance for train versus test subset
set.seed(1234L)
learn <- sample(1:150, 100)
test <- (1:150)[-learn]
rf.fit <- ranger(Species ~ ., data = iris[learn, ], num.trees = 500, write.forest = TRUE)
distanceRandomForest(x = iris[learn, -5], y = iris[test, -5], rfObject = rf.fit, method = "Depth")

CaseBasedReasoning documentation built on May 2, 2023, 9:11 a.m.