XGBoost (R Interface) throwing "label set cannot be empty" error

Question

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.

Answer 1

In python I needed to set the label param in dtrain = xgb.DMatrix(X_train,label=y_train,feature_names=cfg_col_X)

PS I was going to comment but missing rep points.

Answer 2

To train a model you need two things, your training data(a matrix of variables and observations) and your labels (the known classification of each observation in the training data). Perhaps the last column in your data is actually the label? If so you will to vertically split your dtrain so that parameter data= all columns but the last, and a parameter label= just the last column.

Once you have the model, you can use it to predict on data that doesn’t have labels and the output will be the labels.