predict.ELMmboost: SurvELM predict.ELMmboost

In whcsu/SurvELM: Survival Anlalysis with Extreme Learning Machines

Description

Predicting from an Extreme Learning Machine Cox Model with Gradient Based Boosting

Usage

## S3 method for class 'ELMmboost'
predict(object, testx, ...)

Arguments

object	An object that inherits from class ELMmboost.
testx	A data frame in which to look for variables with which to predict.
...	Additional arguments for mboost.

Value

produces a vector of predictions or a matrix of predictions

Author(s)

Hong Wang

See Also

mboost

Examples

set.seed(123)
require(SurvELM)
require(survival)
#Lung DATA
data(lung)
lung=na.omit(lung)
lung[,3]=lung[,3]-1
n=dim(lung)[1]
L=sample(1:n,ceiling(n*0.5))
trset<-lung[L,]
teset<-lung[-L,]
rii=c(2,3)
elmsurvmodel=ELMmboost(x=trset[,-rii],y=Surv(trset[,rii[1]], trset[,rii[2]]))
#THE predicted linear predictor
testpre=predict(elmsurvmodel,teset[,-c(rii)])

whcsu/SurvELM documentation built on Jan. 28, 2020, 3:07 p.m.