get_tree: Fetches a decision tree

In souravc83/fastBoost: a fast implementation of adaboost.M1 and real adaboost

Description

returns a single weak decision tree classifier which is part of the strong classifier returns an individual tree from the adaboost object This can provide the user with some clarity on the individual building blocks of the strong classifier

Usage

get_tree(object, tree_num)

Arguments

object	object of class adaboost
tree_num	integer describing the tree to get

Value

tree object of class rpart

See Also

adaboost

Examples

fakedata <- data.frame( X=c(rnorm(100,0,1),rnorm(100,1,1)), Y=c(rep(0,100),rep(1,100) ) )
fakedata$Y <- factor(fakedata$Y)
A <- adaboost(Y~X, fakedata, 10)
tree <- get_tree(A,5)

souravc83/fastBoost documentation built on May 30, 2019, 6:34 a.m.