使用pdp包对xgboost进行分类的部分依赖图

Question

I use pdp package to run partial dependency for linear regression using xgboost package is perfect without any warning. But when I change to classification(logistic) label for xgboost. I got the warning messages for partial dependency say the partial dependency is based on linear as follows. May I ask if the code has to be revised in somehow to exactly feed classification object using xgboost package so that the partial dependency is correct. Or I can ignore the warning message , it is correct already. I know randomforest is straight forward without any warning messages

# Load required packages
library(pdp)
library(xgboost)

# Simulate training data with ten million records
set.seed(101)
trn <- as.data.frame(mlbench::mlbench.friedman1(n = 1e+07, sd = 1))
trn=trn[sample(nrow(trn), 500), ]
trn$y=ifelse(trn$y>16,1,0)

# Fit an XGBoost classification(logistic) model
set.seed(102)
bst <- xgboost(data = data.matrix(subset(trn, select = -y)),
           label = trn$y,
           objective = "reg:logistic",
           nrounds = 100,
           max_depth = 2,
           eta = 0.1)
 #partial dependency plot

  pd <- partial(bst$handle,
            pred.var = c("x.1"), 
            grid.resolution = 10, 
            train = data.matrix(subset(trn, select = -y)),
            prob=TRUE,
            plot = FALSE,
            .progress = "text")

 Warning message:
 In superType.default(object) :
 `type` could not be determined; assuming `type = "regression"`

Answer 1

In this case, you can safely ignore the warning; however, it did lead me to a small bug in the pdp package for which I will push a fix to shortly. Thanks for reporting!