False positive (FP): Difference between revisions

False positive (FP) (view source)

Revision as of 00:48, 20 February 2023

1 byte removed , 20 February 2023

no edit summary

Interface administrators, Administrators (Semantic MediaWiki), Curators (Semantic MediaWiki), Editors (Semantic MediaWiki), Suppressors, Administrators

7,785

edits

Revision as of 00:48, 20 February 2023 (view source) Alpha5 (talk \| contribs) (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...")		Revision as of 00:48, 20 February 2023 (view source) Alpha5 (talk \| contribs) No edit summary Newer edit →
Line 1:		Line 1:
	===Introduction==		==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 negative outcomes.		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 negative outcomes.