R: Class "RandomForest"

RandomForest-class {party} | R Documentation

## Class "RandomForest"

### Description

A class for representing random forest ensembles.

### Objects from the Class

Objects can be created by calls of the form `new("RandomForest", ...)`.

### Slots

`ensemble`:

  Object of class `"list"`, each element being an object of class `"BinaryTree"`.

`data`:

  an object of class `"ModelEnv"`.

`initweights`:

  a vector of initial weights.

`weights`:

  a list of weights defining the sub-samples.

`where`:

  a matrix of integers vectors of length n (number of observations in the learning sample) giving the number of the terminal node the corresponding observations is element of (in each tree).

`data`:

  an object of class `"ModelEnv"`.

`responses`:

  an object of class `"VariableFrame"` storing the values of the response variable(s).

`cond_distr_response`:

  a function computing the conditional distribution of the response.

`predict_response`:

  a function for computing predictions.

`prediction_weights`:

  a function for extracting weights from terminal nodes.

`get_where`:

  a function for determining the number of terminal nodes observations fall into.

`update`:

  a function for updating weights.

### Methods

treeresponse

  `signature(object = "RandomForest")`: ...

weights

  `signature(object = "RandomForest")`: ...

where

  `signature(object = "RandomForest")`: ...

### Examples

        set.seed(290875)

        ### honest (i.e., out-of-bag) cross-classification of
        ### true vs. predicted classes
        data("mammoexp", package = "TH.data")
        table(mammoexp$ME, predict(cforest(ME ~ ., data = mammoexp,
                                   control = cforest_unbiased(ntree = 50)),
                                   OOB = TRUE))

[Package party version 1.3-7 Index]