Description Usage Arguments Value Note

Carries out the selection step of fuzzyforest algorithm. Returns data.frame with variable importances and top rated features.

1 2 | ```
select_RF(X, y, drop_fraction, number_selected, mtry_factor, ntree_factor,
min_ntree, num_processors, nodesize)
``` |

`X` |
A data.frame. Each column corresponds to a feature vectors. Could include additional covariates not a part of the original modules. |

`y` |
Response vector. |

`drop_fraction` |
A number between 0 and 1. Percentage of features dropped at each iteration. |

`number_selected` |
Number of features selected by fuzzyforest. |

`mtry_factor` |
In the case of regression, |

`ntree_factor` |
A number greater than 1. |

`min_ntree` |
Minimum number of trees grown in each random forest. |

`num_processors` |
Number of processors used to fit random forests. |

`nodesize` |
Minimum nodesize |

A data.frame with the top ranked features.

This work was partially funded by NSF IIS 1251151 and AMFAR 8721SC.

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