dsc2: Check the robustness of a suggested dsc() prediction of X for...

In Antoine-Masse/KefiR: KefiR Package

Check the robustness of a suggested dsc() prediction of X for objectives in Y by bootstrapping

Description

Check the robustness of a suggested dsc() prediction of X for objectives in Y by bootstrapping

Usage

dsc2(data, reg, dsc, iter = 500, plot = TRUE, return = FALSE)

Arguments

data	A data.frame with X(s) and Y(s).
reg	A linear model or a list of linear models.
dsc	A dataframe line containing the X's to be predicted (ideally a dsc() output).
iter	Number of iterations in the scalable approach (should ideally be much greater than the popupulation (pop) of settings.
plot	If TRUE, displays interactive parallel coordinates (plot_ly) to identify the best possible settings.
return	If TRUE, return the data.frame of values predicted by bootstrapping.

Value

A dataframe containing all the selected settings sorted from best (top) to worst (bottom).

Examples

data(mtcars)
colnames(mtcars)
myreg1 <- evolreg(mtcars,"mpg")
myreg2 <- evolreg(mtcars,"cyl")
reg <- list()
reg[[1]] <- myreg1
reg[[2]] <- myreg2
output <- dsc(mtcars,reg,Y=c(23.4,5.4),pop=400,iter=200)
# Bootstrap on the best line with dsc2()
output2 <- dsc2(mtcars,reg,dsc=output[1,],plot=TRUE)

Antoine-Masse/KefiR documentation built on July 4, 2024, 11:40 a.m.