Uses the "partial_dependence" function to plot partial dependence for BRT models. Future work will be into finding a way to generalize these methods to rpart and randomForest models, as an S3 method. This code is bespoke at the moment, and isn't designed as a flexible way to create plots, so I would recommend that people who want to plot their own partial plots just use `partial_dependence` and go from there.
gg_partial_plot(x, vars)
a faceted ggplot plot of the variables
## Not run: ------------------------------------ # # # using gbm.step from the dismo package # # library(gbm) # library(dismo) # # # load data # # data(Anguilla_train) # anguilla_train <- Anguilla_train[1:200,] # # # fit model # angaus_tc_5_lr_01 <- gbm.step(data = anguilla_train, # gbm.x = 3:14, # gbm.y = 2, # family = "bernoulli", # tree.complexity = 5, # learning.rate = 0.01, # bag.fraction = 0.5) # # gg_partial_plot(angaus.tc5.lr01, # var = c("SegSumT", # "SegTSeas")) # ## ---------------------------------------------