`xgb_train()`

and `xgb_predict()`

are wrappers for `xgboost`

tree-based
models where all of the model arguments are in the main function.

## Usage

```
xgb_train(
x,
y,
weights = NULL,
max_depth = 6,
nrounds = 15,
eta = 0.3,
colsample_bynode = NULL,
colsample_bytree = NULL,
min_child_weight = 1,
gamma = 0,
subsample = 1,
validation = 0,
early_stop = NULL,
counts = TRUE,
event_level = c("first", "second"),
...
)
xgb_predict(object, new_data, ...)
```

## Arguments

- x
A data frame or matrix of predictors

- y
A vector (factor or numeric) or matrix (numeric) of outcome data.

- max_depth
An integer for the maximum depth of the tree.

- nrounds
An integer for the number of boosting iterations.

- eta
A numeric value between zero and one to control the learning rate.

- colsample_bynode
Subsampling proportion of columns for each node within each tree. See the

`counts`

argument below. The default uses all columns.- colsample_bytree
Subsampling proportion of columns for each tree. See the

`counts`

argument below. The default uses all columns.- min_child_weight
A numeric value for the minimum sum of instance weights needed in a child to continue to split.

- gamma
A number for the minimum loss reduction required to make a further partition on a leaf node of the tree

- subsample
Subsampling proportion of rows. By default, all of the training data are used.

- validation
The

*proportion*of the data that are used for performance assessment and potential early stopping.- early_stop
An integer or

`NULL`

. If not`NULL`

, it is the number of training iterations without improvement before stopping. If`validation`

is used, performance is base on the validation set; otherwise, the training set is used.- counts
A logical. If

`FALSE`

,`colsample_bynode`

and`colsample_bytree`

are both assumed to be*proportions*of the proportion of columns affects (instead of counts).- event_level
For binary classification, this is a single string of either

`"first"`

or`"second"`

to pass along describing which level of the outcome should be considered the "event".- ...
Other options to pass to

`xgb.train()`

or xgboost's method for`predict()`

.- new_data
A rectangular data object, such as a data frame.