err.abcrf: Calculate and plot for different numbers of tree, the...

In abcrf: Approximate Bayesian Computation via Random Forests

Calculate and plot for different numbers of tree, the out-of-bag errors associated with an ABC-RF object

Description

err.abcrf returns out-of-bag errors and plot them.

Usage

err.abcrf(object, training, paral=FALSE,
ncores= if(paral) max(detectCores()-1,1) else 1)

Arguments

object	an abcrf object.
training	the data frame containing the reference table used to train the abcrf object.
paral	a boolean that indicates if random forests predictions should be parallelized.
ncores	the number of CPU cores to use for the random forest predictions. If paral=TRUE, it is used the number of CPU cores minus 1. If ncores is not specified and detectCores does not detect the number of CPU cores with success then 1 core is used.

Value

A matrix with 2 columns: the number of trees and the out-of-bag errors. Errors are computed from 40 trees to the total number.

References

Pudlo P., Marin J.-M., Estoup A., Cornuet J.-M., Gautier M. and Robert, C. P. (2016) Reliable ABC model choice via random forests Bioinformatics doi: 10.1093/bioinformatics/btv684

See Also

abcrf, predict.abcrf, plot.abcrf

Examples

data(snp)
modindex <- snp$modindex[1:500]
sumsta <- snp$sumsta[1:500,]
data1 <- data.frame(modindex, sumsta)
model.rf <- abcrf(modindex~., data1, ntree=100)
err.rf <- err.abcrf(model.rf, data1)

abcrf documentation built on Aug. 9, 2022, 5:07 p.m.