I am trying to use the XGBoost model to perform a multi-class classification over 40 classes.
The code is as follows:
xgb_params = list(colsample_bytree= 0.7, subsample = 0.7, eta = 0.05, objective= 'multi:softmax', max_depth= 5, min_child_weight= 1, eval_metric= "mlogloss", num_class = categoryclassnos, nthread=4) fit.xgb = xgb.train(params = xgb_params, data = dtrain, nrounds = 500, watchlist = list(train = dtrain, test=dtest), print_every_n = 50)
However, I am getting the following error:
Check failed: (info.labels.size()) != (0) label set cannot be empty
I have reproduced the dataset and the R script here.
Any help/ pointers are deeply appreciated.