`R/GradientBoostingMachine.R`

`setGradientBoostingMachine.Rd`

Create setting for gradient boosting machine model using gbm_xgboost implementation

setGradientBoostingMachine(ntrees = c(100, 1000), nthread = 20, earlyStopRound = 25, maxDepth = c(4, 6, 17), minRows = 2, learnRate = c(0.005, 0.01, 0.1), seed = NULL)

ntrees | The number of trees to build |
---|---|

nthread | The number of computer threads to (how many cores do you have?) |

earlyStopRound | If the performance does not increase over earlyStopRound number of interactions then training stops (this prevents overfitting) |

maxDepth | Maximum number of interactions - a large value will lead to slow model training |

minRows | The minimum number of rows required at each end node of the tree |

learnRate | The boosting learn rate |

seed | An option to add a seed when training the final model |