decisionStump: Decision Stump Algorithm

In freestats: Statistical algorithms used in common data mining course

Description

Do classification with tree method in one step

Usage

decisionStump(X, w, y)

Arguments

X	Data matrix / Data frame
w	Weight that given to each observation. Used in calculate cost function.
y	Class label for data points in X, must be -1 or 1

Value

j	The best dimention to cut the tree
theta	Value that seperate tree in the best dimention
m	the routine label value (for now only 1)

Author(s)

Xiaoyao Yang

Examples

set.seed(1024)
z <- runif(n=5)
mydata <- fakedata(w=z,n=100)
X<- mydata$S[,1:4]
y <- mydata$y
w <- rep(1/100,100)
pars <- decisionStump(X=X,w=w,y=y)

Example output

freestats documentation built on May 2, 2019, 1:18 p.m.