get.tree.forestRK: Extracts the structure of one or more trees in a forestRK...

In forestRK: Implements the Forest-R.K. Algorithm for Classification Problems

Description

Extracts structure of one or more trees from a forestRK object.

Each tree in the list are named by the exact indices of the tree; for example, if the code obj <- get.tree.forestRK(forestRK.1, tree.index=c(4,5,6)) was used to extract the structure of the 4th, 5th, and 6th trees in the forest, the user can retrieve the information pertains explicitly to the 4th tree in the forest by doing obj["4"]].

Usage

 get.tree.forestRK(forestRK.object = forestRK(), tree.index=c())

Arguments

forestRK.object	a forestRK object.
tree.index	a vector of indices of the trees that we want to extract from the forestRK object.

Value

A list containing forestRK trees that have their indices specified in the function argument tree.index.

Author(s)

Hyunjin Cho, [e-mail] Rebecca Su, [e-mail]

See Also

forestRK

Examples

  ## example: iris dataset
  ## load the forestRK package
  library(forestRK)

  x.train <- x.organizer(iris[,1:4], encoding = "num")[c(1:25,51:75,101:125),]
  y.train <- y.organizer(iris[c(1:25,51:75,101:125),5])$y.new

  # random forest
  # min.num.obs.end.node.tree is set to 5 by default;
  # entropy is set to TRUE by default
  # normally nbags and samp.size have to be much larger than 30 and 50
  forestRK.1 <- forestRK(x.train, y.train, nbags = 30, samp.size = 50)

  # get tree
  tree.index.ex <- c(1,3,8)
  get.tree <- get.tree.forestRK(forestRK.1, tree.index = tree.index.ex)
  get.tree[["8"]] # display the 8th tree of the random forest

forestRK documentation built on July 19, 2019, 5:04 p.m.