logforest | R Documentation |

Constructs an ensemble of logic regression models using bagging for classification and identification of important predictors and predictor interactions

```
logforest(resp, Xs, nBSXVars, anneal.params, nBS=100, h=0.5, norm=TRUE, numout=5, nleaves)
```

`resp` |
numeric vector of binary response values |

`Xs` |
matrix or dataframe of zeros and ones for all predictor variables |

`nBSXVars` |
integer for the number of predictors used to construct each logic regression model. The default value is all predictors in the data. |

`anneal.params` |
a list containing the parameters for simulated annealing. See the help file for the function |

`nBS` |
number of logic regression trees to be fit in the logic forest model. |

`h` |
a number between 0 and 1 for the minimum proportion of trees in the logic forest that must predict a 1 for the prediction to be one. |

`norm` |
logical. If FALSE, predictor and interaction scores in model output are not normalized to range between zero and one. |

`numout` |
number of predictors and interactions to be included in model output |

`nleaves` |
the maximum number of end nodes generated for each tree |

An object of class `"logforest"`

including a list of values

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