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Table 1 Confusion matrix show to summarizes the total number of correct and incorrect predictions and actual positive and negative

From: Machine learning to predict virological failure among HIV patients on antiretroviral therapy in the University of Gondar Comprehensive and Specialized Hospital, in Amhara Region, Ethiopia, 2022

 

Predictive negative

Predictive positive

Actual negative

True Negative (TN)

False Positive (FP)

Actual positive

False Negative (FN)

True Positive (TP)

  1. From the above confusion matrix, the term was described as:
  2. True positives (TP): the actual true positives that were correctly predicted as true positives
  3. True negatives (TN): the actual true negatives that were correctly predicted as true negatives
  4. False negatives (FN): the actual positives that were incorrectly predicted as false negatives
  5. False positives (FP): The actual negatives that were incorrectly predicted as positives
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BMC Medical Informatics and Decision Making

ISSN: 1472-6947

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