Description Usage Arguments Details Value Author(s) References See Also Examples
This function is used to evaluate a test set for a pre-trained GPD classifier. It can be used to perform open set classification based on the generalized Pareto distribution.
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train |
data matrix containing the train data. Class labels should not be included. |
test |
a data matrix containing the test data. |
pre |
a list 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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