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

This function is used to evaluate a test set for a pre-trained GEV classifier. It can be used to perform open set classification based on the generalized Pareto distribution.

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`train` |
a data matrix containing the train data. Class labels should not be included. |

`test` |
a data matrix containing the test data. |

`pre` |
a numeric vector of parameters obtained with the function |

`prob` |
logical indicating whether p-values should be returned. |

`alpha` |
threshold to be used if |

For details on the method and parameters see Vignotto and Engelke (2018).

If `prob`

is equal to `TRUE`

, a vector containing the p-values for each point is returned. A high p-value results in the classification of the corresponding test data as a known point, since this hypothesis cannot be rejected. If the p-value is small, the corresponding test data is classified as an unknown point. If `prob`

is equal to `TRUE`

, a vector of predicted values is returned.

Edoardo Vignotto

edoardo.vignotto@unige.ch

Vignotto, E., & Engelke, S. (2018). Extreme Value Theory for Open Set Classification-GPD and GEV Classifiers. *arXiv preprint arXiv:1808.09902*.

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