xgb_train is a wrapper for
xgboost tree-based models where all of the
model arguments are in the main function.
xgb_train( x, y, max_depth = 6, nrounds = 15, eta = 0.3, colsample_bytree = 1, min_child_weight = 1, gamma = 0, subsample = 1, validation = 0, early_stop = NULL, ... )
A data frame or matrix of predictors
A vector (factor or numeric) or matrix (numeric) of outcome data.
An integer for the maximum depth of the tree.
An integer for the number of boosting iterations.
A numeric value between zero and one to control the learning rate.
Subsampling proportion of columns.
A numeric value for the minimum sum of instance weights needed in a child to continue to split.
A number for the minimum loss reduction required to make a further partition on a leaf node of the tree
Subsampling proportion of rows.
A positive number. If on
An integer or
Other options to pass to