Xsurv_predict: This function allows you to transform survival prediction...

In topycyao/Xsurv: A package used to model survival data from advanced machine learning algorithms

This function allows you to transform survival prediction from risk score to survival time.

Description

This function allows you to transform survival prediction from risk score to survival time.

Usage

Xsurv_predict(model, x_train, y_train, x_test, nc = 25, nq = 0.8)

Arguments

model	xgboost or lightgbm model object
x_train	X train data set
y_train	Y trian data set
x_test	X test data set
nc	number of cutting points defaut is 25, and 20-30 is recommended
nq	quantile of train data time in each cut group for prediction time

Value

predicted survival time

Examples

#example
library(survival)
library(Xsurv)
data(lung)

mydata<-(lung[,-1])
mydata[,2]<-mydata[,2]-1
length(mydata[,1])
names(mydata)<-colnames(mydata)
datay_train<-mydata[1:180,c(1,2)]
datax_train<-mydata[1:180,-c(1,2)]
datay_test<-mydata[181:228,c(1,2)]
datax_test<-mydata[181:228,-c(1,2)]
xs<-Xsurv(datax_train,datay_train,top_n = 5,cp=0.01)

#xs<-Xsurv.cv(datax_train,datay_train,top_n=5)
xm<-xs$model
xtree<-xs$tree
x_ctree<-xtree$tree2
#plot(x_ctree)
shap=xs$SHAP

shap

risk=xs$risk
fit=risk$fit

#plot(fit)
#prediction

pre_time<-pre<-Xsurv_predict(xm,datax_train,datay_train,datax_test)

#predict survival probabilty

pre_x<-Xsurv_predict_sv(xm,datax_train,datay_train,datax_test[1,])

plot(pre_x)

topycyao/Xsurv documentation built on Aug. 6, 2022, 9:06 p.m.