`R/RandomForest.R`

`setRandomForest.Rd`

Create setting for random forest model with python (very fast)

setRandomForest(mtries = -1, ntrees = 500, maxDepth = c(4, 10, 17), varImp = T, seed = NULL)

mtries | The number of features to include in each tree (-1 defaults to square root of total features) |
---|---|

ntrees | The number of trees to build |

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

varImp | Perform an initial variable selection prior to fitting the model to select the useful variables |

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

# NOT RUN { model.rf <- setRandomForest(mtries=c(-1,5,20), ntrees=c(10,100), maxDepth=c(5,20)) # }