rf_filter | R Documentation |

Fits a random forest model and ranks variables by variable importance.

rf_filter( y, x, nfilter = NULL, type = c("index", "names", "full"), ntree = 1000, mtry = ncol(x) * 0.2, ... )

`y` |
Response vector |

`x` |
Matrix of predictors |

`nfilter` |
Number of predictors to return. If |

`type` |
Type of vector returned. Default "index" returns indices, "names" returns predictor names, "full" returns a named vector of variable importance. |

`ntree` |
Number of trees to grow. See randomForest. |

`mtry` |
Number of predictors randomly sampled as candidates at each split. See randomForest. |

`...` |
Optional arguments passed to randomForest. |

This filter uses the randomForest function from the randomForest package. Variable importance is calculated using the importance function, specifying type 1 = mean decrease in accuracy. See importance.

Integer vector of indices of filtered parameters (type = "index") or
character vector of names (type = "names") of filtered parameters. If
`type`

is `"full"`

a named vector of variable importance is returned.

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