问题
I'm doing variable selection with the Boruta package in R. Boruta gives me the standard series of boxplots in a single graph, which is useful, but given the fact that I have too many predictors, I am hoping to be able to limit the number of boxplots that appear in the boruta plot. Something like the following image.
Basicacly, I want to "zoom" on the right end of the plot, but have no idea how to do that with the boruta plot object.
Thanks,
MR
回答1:
Sounds like an simple question, the solution seems surprisingly convoluted. Perhaps somebody can come up with a quicker/more elegant way...
Here, I create a new function based on the source function plot.Boruta
, and add a function argument pars
that takes the names of variables/predictors that we'd like to include in the plot.
As an example, I use the iris
dataset to fit a model.
# Fit model to the iris dataset
library(Boruta);
fit <- Boruta(Species ~ ., data = iris, doTrace = 2);
The function generateCol
is internally called by plot.Boruta
, but is not exported and therefore not available outside of the package. However, we need the function for our revised plot.Boruta
routine.
# generateCol is needed by plot.Boruta
generateCol<-function(x,colCode,col,numShadow){
#Checking arguments
if(is.null(col) & length(colCode)!=4)
stop('colCode should have 4 elements.');
#Generating col
if(is.null(col)){
rep(colCode[4],length(x$finalDecision)+numShadow)->cc;
cc[c(x$finalDecision=='Confirmed',rep(FALSE,numShadow))]<-colCode[1];
cc[c(x$finalDecision=='Tentative',rep(FALSE,numShadow))]<-colCode[2];
cc[c(x$finalDecision=='Rejected',rep(FALSE,numShadow))]<-colCode[3];
col=cc;
}
return(col);
}
We now modify plot.Boruta
, and add a function parameter pars
, by which we filter our list of variables.
# Modified plot.Boruta
plot.Boruta.sel <- function(
x,
pars = NULL,
colCode = c('green','yellow','red','blue'),
sort = TRUE,
whichShadow = c(TRUE, TRUE, TRUE),
col = NULL, xlab = 'Attributes', ylab = 'Importance', ...) {
#Checking arguments
if(class(x)!='Boruta')
stop('This function needs Boruta object as an argument.');
if(is.null(x$ImpHistory))
stop('Importance history was not stored during the Boruta run.');
#Removal of -Infs and conversion to a list
lz <- lapply(1:ncol(x$ImpHistory), function(i)
x$ImpHistory[is.finite(x$ImpHistory[,i]),i]);
colnames(x$ImpHistory)->names(lz);
#Selection of shadow meta-attributes
numShadow <- sum(whichShadow);
lz <- lz[c(rep(TRUE,length(x$finalDecision)), whichShadow)];
#Generating color vector
col <- generateCol(x, colCode, col, numShadow);
#Ordering boxes due to attribute median importance
if (sort) {
ii <- order(sapply(lz, stats::median));
lz <- lz[ii];
col <- col[ii];
}
# Select parameters of interest
if (!is.null(pars)) lz <- lz[names(lz) %in% pars];
#Final plotting
graphics::boxplot(lz, xlab = xlab, ylab = ylab, col = col, ...);
invisible(x);
}
Now all we need to do is call plot.Boruta.sel
instead of plot
, and specify the variables that we'd like to include.
plot.Boruta.sel(fit, pars = c("Sepal.Length", "Sepal.Width"));
来源:https://stackoverflow.com/questions/47342553/boruta-box-plots-in-r