In a two-class problem, a classification model makes two types of error: false positives and false negatives. A false positive is an example of negative class that has been incorrectly classified as positive. See confusion matrix for a complete range of related terms.
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(2011). False Positive. In: Sammut, C., Webb, G.I. (eds) Encyclopedia of Machine Learning. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-30164-8_300
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DOI: https://doi.org/10.1007/978-0-387-30164-8_300
Publisher Name: Springer, Boston, MA
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