I just came across your This Machine Learning Project on Imbalanced Data Can Add Value to Your Resume article and i am tryng to run the same in my Rstudio. I got the below error while running the code in this line
xgb_tune <- tuneParams(learner = xgb_learner, task = train.task, resampling = set_cv,
measures = list(acc,tpr,tnr,fpr,fp,fn), par.set = xg_ps, control = rancontrol)
The dataset has both factor and numeric variables
[Tune-x] 1: max_depth=5; lambda=0.146; eta=0.374; subsample=0.841; min_child_weight=8.23; colsample_bytree=0.587
Error in checkLearnerBeforeTrain(task, learner, weights) :
Task ‘d_train’ has factor inputs in ‘age, wage_per_hour, capital_gains, capital_loss…’, but learner ‘classif.xgboost’ does not support that!