Indicwiki: 1 revision imported from :alpha:Template:Diagnostic_testing_diagram

2023-04-06T04:37:21Z

1 revision imported from alpha:Template:Diagnostic_testing_diagram

← Older revision	Revision as of 10:07, 6 April 2023
(No difference)

alpha>Indicwiki: Created page with "{| class="wikitable" align="center" style="border:none; background:transparent; text-align:center;" | style="border:none;" rowspan="2" | | style="border:none;" | | style="back..."

2023-03-21T05:15:14Z

Created page with "{| class="wikitable" align="center" style="border:none; background:transparent; text-align:center;" | style="border:none;" rowspan="2" | | style="border:none;" | | style="back..."

New page

{| class="wikitable" align="center" style="border:none; background:transparent; text-align:center;"
| style="border:none;" rowspan="2" |
| style="border:none;" |
| style="background:#bbeeee;" colspan="2" | '''Predicted condition'''
| style="border:none; text-align:right;" colspan="2" | Sources: <ref>
{{cite journal |last=Balayla |first=Jacques |title=Prevalence threshold (ϕe) and the geometry of screening curves |journal=PLoS One |date=2020 |volume=15 |issue=10 |doi=10.1371/journal.pone.0240215 |url=https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0240215}}</ref><ref>
{{cite journal |last=Fawcett |first=Tom |title=An Introduction to ROC Analysis |journal=Pattern Recognition Letters |date=2006 |volume=27 |issue=8 |pages=861–874 |doi=10.1016/j.patrec.2005.10.010 |url=http://people.inf.elte.hu/kiss/11dwhdm/roc.pdf}}</ref><ref>
{{Cite journal|last1=Piryonesi S. Madeh|last2=El-Diraby Tamer E.|date=2020-03-01|title=Data Analytics in Asset Management: Cost-Effective Prediction of the Pavement Condition Index|journal=Journal of Infrastructure Systems|volume=26|issue=1|pages=04019036|doi=10.1061/(ASCE)IS.1943-555X.0000512}}</ref><ref>
{{cite journal |first=David M. W. |last=Powers |date=2011 |title=Evaluation: From Precision, Recall and F-Measure to ROC, Informedness, Markedness & Correlation |journal=Journal of Machine Learning Technologies |volume=2 |issue=1 |pages=37–63 |url=https://www.researchgate.net/publication/228529307}}</ref><ref>
{{cite book |last=Ting |first=Kai Ming |editor2-first=Geoffrey I. |editor2-last=Webb |editor1-first=Claude |editor1-last=Sammut |title=Encyclopedia of machine learning |date=2011 |publisher=Springer |doi=10.1007/978-0-387-30164-8 |isbn=978-0-387-30164-8 }}</ref><ref>
{{cite web |url=https://www.cawcr.gov.au/projects/verification/ |title=WWRP/WGNE Joint Working Group on Forecast Verification Research |last1=Brooks |first1=Harold |last2=Brown |first2=Barb |last3=Ebert |first3=Beth |last4=Ferro |first4=Chris |last5=Jolliffe |first5=Ian |last6=Koh |first6=Tieh-Yong |last7=Roebber |first7=Paul |last8=Stephenson |first8=David |date=2015-01-26|website=Collaboration for Australian Weather and Climate Research|publisher=World Meteorological Organisation|access-date=2019-07-17}}</ref><ref>
{{cite journal |vauthors = Chicco D, Jurman G |title = The advantages of the Matthews correlation coefficient (MCC) over F1 score and accuracy in binary classification evaluation |journal = BMC Genomics |volume = 21 |issue = 1 |date = January 2020 |page = 6-1–6-13 |pmid = 31898477 |doi = 10.1186/s12864-019-6413-7 |pmc = 6941312}}</ref><ref>
{{cite journal |vauthors = Chicco D, Toetsch N, Jurman G |title = The Matthews correlation coefficient (MCC) is more reliable than balanced accuracy, bookmaker informedness, and markedness in two-class confusion matrix evaluation |journal = BioData Mining |volume = 14 |issue = 13 |date = February 2021 |page = 1-22 |pmid = 33541410 | pmc = 7863449 |doi = 10.1186/s13040-021-00244-z}}</ref><ref>
{{cite journal |author = Tharwat A. |title = Classification assessment methods |journal = Applied Computing and Informatics |date = August 2018 |doi = 10.1016/j.aci.2018.08.003 |doi-access = free }}</ref> {{navbar|Diagnostic testing diagram|plain=y}}
|-
| style="background:#eeeeee;" | [[Statistical population|Total population]] = P + N
| style="background:#ccffff;" | '''Positive (PP)'''
| style="background:#aadddd;" | '''Negative (PN)'''
| style="border-left:double silver;" | [[Youden's_J_statistic|Informedness]], {{small|bookmaker informedness (BM)}} = TPR + TNR − 1
| [[Prevalence threshold]] (PT) =<math>\mathsf\tfrac{\sqrt{\text{TPR}\times\text{FPR}}-\text{FPR}}{\text{TPR}-\text{FPR}}</math>
|-
| rowspan="2" {{verth|va=middle|cellstyle=background:#eeeebb;|'''Actual condition'''}}
| style="background:#ffffcc;" | '''Positive (P)'''
| style="background:#ccffcc;" | '''[[True positive]] (TP), {{small|hit}}'''
| style="background:#ffdddd;" | '''[[False negative]] (FN), {{small|[[type II error]], miss, underestimation}}'''
| style="background:#eeffee;" | [[True positive rate]] (TPR), [[recall (information retrieval)|recall]], [[Sensitivity (tests)|sensitivity]] (SEN), {{small|probability of detection, hit rate, [[statistical power|power]]}} = {{sfrac|TP|P}} = 1 − FNR
| style="background:#ffeeee;" | [[False negative rate]] (FNR), {{small|miss rate}} = {{sfrac|FN|P}} = 1 − TPR
|-
| style="background:#ddddaa;" | '''Negative (N)'''
| style="background:#ffcccc;" | '''[[False positive]] (FP), {{small|[[type I error]], false alarm, overestimation}}'''
| style="background:#bbeebb;" | '''[[True negative]] (TN), {{small|correct rejection}}'''
| style="background:#eedddd;" | [[False positive rate]] (FPR), {{small|probability of false alarm, [[evaluation measures (information retrieval)#Fall-out|{{nowrap|fall-out}}]]}} = {{sfrac|FP|N}} = 1 − TNR
| style="background:#ddeedd;"| [[True negative rate]] (TNR), {{small|[[specificity (tests)|specificity]] (SPC), selectivity}} = {{sfrac|TN|N}} = 1 − FPR
|-
| style="border:none;" rowspan="3"|
| style="border-top:double silver; border-right:double silver;"|[[Prevalence]] = {{sfrac|P|P + N}}
| style="background:#eeffee;" | {{nowrap|[[Positive predictive value]] (PPV),}} {{small|[[precision (information retrieval)|precision]]}} = {{sfrac|TP|PP}} = 1 − FDR
| style="background:#ffeeee;border-right:double silver;"|[[False omission rate]] (FOR) = {{sfrac|FN|PN}} = 1 − NPV
| style="background:#eeeeff;" | [[Positive likelihood ratio]] (LR+) = {{sfrac|TPR|FPR}}
| style="background:#eeeeff;" | [[Negative likelihood ratio]] (LR−) = {{sfrac|FNR|TNR}}
|-
| style="border-right:double silver;"|[[Accuracy and precision#In binary classification|Accuracy]] (ACC) = {{sfrac|TP + TN|P + N}}
| style="background:#eedddd;"|[[False discovery rate]] (FDR) = {{sfrac|FP|PP}} = 1 − PPV
| style="background:#ddeedd;"|[[Negative predictive value]] (NPV) = {{sfrac|TN|PN}} = 1 − FOR
| style="border-top:double silver;border-right:double silver;" | [[Markedness]] (MK), {{small|deltaP (Δp)}} = PPV + NPV − 1
| style="background:#eeeeff;" | [[Diagnostic odds ratio|Diagnostic {{nowrap|odds ratio}}]] (DOR) = {{sfrac|LR+|LR−}}
|-
| Balanced accuracy (BA) = {{sfrac|TPR + TNR|2}}
| style="border-top:double silver;"|[[F1 score|F1 score]] = {{sfrac|2&hairsp;PPV&hairsp;×&hairsp;TPR|PPV + TPR}} = {{sfrac|2&hairsp;TP|2&hairsp;TP + FP + FN}}
| style="border-top:double silver;"|[[Fowlkes–Mallows index]] (FM) = <math>\scriptstyle\mathsf\sqrt{\text{PPV}\times\text{TPR}}</math>
| style="border-top:double silver;"|[[Matthews correlation coefficient]] (MCC) =<math>\scriptstyle\mathsf\sqrt{\text{TPR}\times\text{TNR}\times\text{PPV}\times\text{NPV}}</math><math>\scriptstyle-\mathsf\sqrt{\text{FNR}\times\text{FPR}\times\text{FOR}\times\text{FDR}}</math>
| style="border-top:double silver;" colspan="2"|Threat score (TS), critical success index (CSI), [[Jaccard_index#Jaccard_index_in_binary_classification_confusion_matrices|Jaccard index]] = {{sfrac|TP|TP + FN + FP}}
|}

Template:Diagnostic testing diagram - Revision history

Indicwiki: 1 revision imported from :alpha:Template:Diagnostic_testing_diagram

alpha>Indicwiki: Created page with "{| class="wikitable" align="center" style="border:none; background:transparent; text-align:center;" | style="border:none;" rowspan="2" | | style="border:none;" | | style="back..."