noun
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Types of error in data reporting, where false positive is an error in which a test result incorrectly indicates the presence of a condition, while a false negative is the opposite error where the test fails to indicate the actual presence
A false positive is an error in binary classification in which a test result incorrectly indicates the presence of a condition (such as a disease when the disease is not present), while a false negative is the opposite error, where the test result incorrectly indicates the absence of a condition when it is actually present. These are the two kinds of errors in a binary test, in contrast to the two... Wikipedia
