Hello,

I am trying to implement xgboost in R for a classification problem:

```
# xgboost parameters
param <- list("objective" = "binary:logistic", # binary classification
"eval_metric" = "error", # evaluation metric
"nthread" = 8, # number of threads to be used
"max_depth" = 16, # maximum depth of tree
"eta" = 0.2, # step size shrinkage
"gamma" = 0, # minimum loss reduction
"subsample" = 1, # part of data instances to grow tree
"colsample_bytree" = 1, # subsample ratio of columns when constructing each tree
"min_child_weight" = 12) # minimum sum of instance weight needed in a child
# Split back into test and train sets
train_xg <- combi_fg[1:891,]
test_xg <- combi_fg[892:1309,]
#Convert the data to matrix form:
#Convert the train_xg:
train.matrix = as.matrix(train_xg)
mode(train.matrix) = "numeric"
#Convert the test_xg:s
test.matrix = as.matrix(test_xg)
mode(test.matrix) = "numeric"
# k-fold cross validation, with timing
nround.cv = 200
xgboost.cv <- xgb.cv(param=param, data=train.matrix, label=train$Survived,
nfold=10, nrounds=nround.cv, prediction=TRUE, verbose=T)
```

However when I am trying to predict on the test data using:

`pred <- predict(xgboost.cv,test.matrix)`

I am getting an error:

Why is this error coming and how to resolve it??