Description Usage Arguments Value

`xgb_train`

is a wrapper for `xgboost`

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

1 2 3 4 5 6 7 8 9 10 11 12 13 14 |

`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_bytree` |
Subsampling proportion of 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. |

`validation` |
A positive number. If on |

`early_stop` |
An integer or |

`...` |
Other options to pass to |

A fitted `xgboost`

object.

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