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False positive (FP): Difference between revisions
Created page with "===Introduction== Machine learning models utilize classification to detect different patterns in data and make predictions based on them. False positive (FP) refers to a situation when the model predicts an event has taken place but it wasn't true; this can happen when it recognizes a pattern similar to what was desired but which does not match exactly. FPs have serious repercussions, especially within healthcare where misdiagnosis could lead to incorrect treatments and..."
(Created page with "===Introduction== Machine learning models utilize classification to detect different patterns in data and make predictions based on them. False positive (FP) refers to a situation when the model predicts an event has taken place but it wasn't true; this can happen when it recognizes a pattern similar to what was desired but which does not match exactly. FPs have serious repercussions, especially within healthcare where misdiagnosis could lead to incorrect treatments and...") |
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