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False positives and false negatives

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…

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False positive error

False negative error

Related terms

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False positives and false negatives

Nodes26
Edges25
Triples0
Avg. degree1.92
Density0.076923
Components1

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false positive test result negative error rate hypothesis statistical condition probability type indicates errors testing p-value given risk known present

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