Description Usage Arguments Details Value Author(s) References See Also

Partial dependence plot gives a graphical depiction of the marginal effect of a variable on the response variable.

1 2 3 4 |

`x, ` |
an object of class |

`pred.data, ` |
a data frame used for contructing the plot, usually the training data used to contruct the random forest. |

`x.var, ` |
name of the variable for which partial dependence is to be examined. |

`offset, ` |
a vector, the corresponding log-exposures of pred.data. |

`w, ` |
weights to be used in averaging; if not supplied, mean is not weighted |

`plot, ` |
whether the plot should be shown on the graphic device. |

`n.pt, ` |
if |

`rug, ` |
whether to draw hash marks at the bottom of the plot indicating the deciles of |

`xlab, ` |
label for the x-axis. |

`ylab, ` |
label for the y-axis. |

`main, ` |
main title for the plot. |

`..., ` |
other graphical parameters to be passed on to |

The function being plotted is defined as:

*f(x) = 1/n* ∑_{i=1}^{n} f(x, x_{iC})*

, where x is the variable for which partial dependence is sought, and x_iC is the other variables in the data.

A list with two components: `x`

and `y`

, which are the values used in the plot.
The `rfCountData`

object must contain the forest component; i.e.,
created with `rfPoisson(..., keep.forest=TRUE)`

. This function runs quite slow for large data sets.

Andy Liaw andy_liaw@merck.com

Friedman, J. (2001). Greedy function approximation: the gradient boosting machine, Ann. of Stat.

rfPoisson

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