# Perform generic out-of-bag error analysis.

### Description

If performing regression, calculate which out-of-bag residuals and MSE. Otherwise, calculate which out-of-bag observations were classified correctly, what the overall misclassification rate is, as well as the confusion matrix.

### Usage

1 | ```
defaultOOBPerformanceAnalysis(prediction, response, oobObs)
``` |

### Arguments

`prediction` |
a vector of predicted responses. |

`response` |
a vector of true response. |

`oobObs` |
a vector of indices which values in |

### Value

If performing regression, return a list with components:

`oobMSE` |
the out-of-bag mean squared error. |

`resVec` |
a vector of length |

Otherwise, return a list with components:

`oobErr` |
overall misclassification rate. |

`oobConfMat` |
the confusion matrix of out-of-bag predictions against the true class labels. |

`errVec` |
a vector of length |

### See Also

Other performance analyzers: `boost`

,
`boost.function`

, `boost.list`