uncertainty: Calculate the Uncertainty (95 percent confidence interval) of...

In APML: An Approach for Machine-Learning Modelling

Calculate the Uncertainty (95 percent confidence interval) of Risk Ratio Based on Threshold.

Description

Calculate the uncertainty (95 percent confidence interval) of risk ratio with prediction from general models based on threshold.

Usage

uncertainty(x,y,th,ref=0)

Arguments

x	A vector representing the risk factor.
y	A vector representing the outcome prediction probability.
th	Threshold for dividing the risk facot into two groups.
ref	Reference indicator. If 0, set the group lower than threshold as reference. Default:0

Details

This is used to calculate the risk ratio, but not for odd ratio.

Value

Uncertainty (95 percent confidence interval) of risk ratio.

References

Díaz-Francés, E., Rubio, F.J. On the existence of a normal approximation to the distribution of the ratio of two independent normal random variables. Stat Papers 54, 309-C323 (2013).

Examples

library(h2o)
data(iris)
attach(iris)
h2o.init()
hyper <- list(ntrees=c(2,3,5))
iris <- iris[1:100,c(5,1:4)]
idx <- sample(100,50)
traindata <- iris[idx,]
testdata <- iris[-idx,]
xcol <- names(iris)[2:5]
results <- APML(xcol=xcol,hyper=hyper,
                traindata=traindata,testdata=testdata,
                sort_by ='auc',distribution = 'bernoulli')
data <- as.h2o(iris)
pred<- h2o.predict(results$bestmodel,newdata=data)
data <- h2o.cbind(data,pred)
data <- as.data.frame(data)
plots <- expl_rr(data,setosa~Sepal.Length,ref = 'mean')
uncertainty(data$Sepal.Length,data$setosa,plots$threshold)
h2o.shutdown(prompt=FALSE)
Sys.sleep(2)

APML documentation built on May 12, 2022, 9:06 a.m.