如何使用 R 中的 pdp 来计算 3d 部分依赖图？

Question

I have a Random forest model in R similar to this:

library("randomForest")
library("caret")
library("pdp")
data("cars")
my_data<-cars[1:5]
my_rf <- randomForest( Price ~ ., data=my_data)
price_mil<- partial(my_rf, pred.var = c("Price", "Mileage"))
plotPartial(price_mil, levelplot = FALSE, zlab = "Price", colorkey = TRUE)

However, I would like to have some 3d partial dependence plots, including the values of parameters on the axis. How can I do this with pdp ?

Answer 1

First of all, In your example you used "price" in the partial() function. This does not make sense to me, as you essentially just plot a 2d partial dependence plot that way. I changed that in my example code below.

However, to get the requested partial plots you can use

plotPartial(price_mil, zlab = "Price", levelplot = F, scale = list(arrows = F))

If you want to have more control, I would advise to use the underlying functions of the package to construct your formula and wireframe object and then call wireframe() with scale=list(arrows = F) to add the values to the axes.

library("randomForest")
library("caret")
library("pdp")
data("cars")
my_data <- cars[1:5]
my_rf <- randomForest( Price ~ ., data=my_data)

object <- pdp::partial(my_rf, pred.var = c("Cylinder", "Mileage"))

form <- stats::as.formula(paste("yhat ~", paste(names(object)[1L:2L], 
                                                collapse = "*")))

wireframe(form, data = object, drape =T, zlab = "Price", scale = list(arrows = F))

yields