dsc2 | R Documentation |
Check the robustness of a suggested dsc() prediction of X for objectives in Y by bootstrapping
dsc2(data, reg, dsc, iter = 500, plot = TRUE, return = FALSE)
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. |
A dataframe containing all the selected settings sorted from best (top) to worst (bottom).
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)
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