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  2. False negative
    • According to 3 sources
    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.
    What is the opposite of false positive? Need antonyms for false positive? Here's a list of opposite words from our thesaurus that you can use instead. Noun Opposite of untrue indication of presence or occurrence false negative type II error
    1 opposite of false positive - words and phrases with opposite meaning false negative
     
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    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. … See more

    A false positive error, or false positive, is a result that indicates a given condition exists when it does not. For example, a pregnancy test which indicates a woman is pregnant when she is not, or the conviction of an … See more

    A false negative error, or false negative, is a test result which wrongly indicates that a condition does not hold. For example, when a pregnancy … See more

    False positive and false negative rates
    The false positive rate (FPR) is the proportion of all negatives that still yield positive test outcomes, i.e., the conditional probability of a positive test result given an event that was not present.
    The false positive … See more

     
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  6. WEBJul 21, 2017 · If I say "you do not have cancer," then you cannot determine you do have it until some event causes you to become aware you really do have cancer. Validation requires more information. A false positive …

  7. WEBIn statistics, a false positive is usually called a Type I error. A type I error is when you incorrectly reject the null hypothesis . This creates a “false positive” for your research, leading you to believe that your hypothesis

  8. WEBApr 18, 2021 · What is False positive and False negative? Example of Sensitivity and specificity. Tabulated Results. Positive Predictive Value (PPV) and Negative Predictive Value (NPV) Calculation. References …

  9. WEBApr 17, 2018 · A false positive (type I error) — when you reject a true null hypothesis — or a false negative (type II error) — when you accept a false null hypothesis? I read in many places that the answer to this question …

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