RAB: real adaboost (Friedman et al)

In lgatto/MLInterfaces: Uniform interfaces to R machine learning procedures for data in Bioconductor containers

Description

read adaboost ... a demonstration version

Usage

RAB(formula, data, maxiter=200, maxdepth=1)

Arguments

formula	formula – the response variable must be coded -1, 1
data	data
maxiter	maxiter
maxdepth	maxdepth – passed to rpart

Value

an instance of raboostCont

Author(s)

Vince Carey <[e-mail]>

References

Friedman et al Ann Stat 28/2 337

Examples

library(MASS)
data(Pima.tr)
data(Pima.te)
Pima.all = rbind(Pima.tr, Pima.te)
tonp = ifelse(Pima.all$type == "Yes", 1, -1)
tonp = factor(tonp)
Pima.all = data.frame(Pima.all[,1:7], mtype=tonp)
fit1 = RAB(mtype~ped+glu+npreg+bmi+age, data=Pima.all[1:200,], maxiter=10, maxdepth=5)
pfit1 = Predict(fit1, newdata=Pima.tr)
table(Pima.tr$type, pfit1)

lgatto/MLInterfaces documentation built on May 21, 2019, 5:12 a.m.