2024年1月25日 (四) 04:51 Zeroclanzhang

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2024年1月25日 (四) 04:51 Zeroclanzhang

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Zeroclanzhang：创建页面，内容为“{| 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" | '''预测条件''' | style="border:none; text-align:right;" colspan="2" | ^来源: {{cite journal |last=Balayla |first=Jacques |title=流行阈值 (ϕe) 及筛查曲线的几何性质 |journal=PLOS ONE |date=2020 |volume=15 |issue=1…”

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创建页面，内容为“<noinclude>{| 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" | '''预测条件''' | style="border:none; text-align:right;" colspan="2" | 来源: <ref> {{cite journal |last=Balayla |first=Jacques |title=流行阈值 (ϕe) 及筛查曲线的几何性质 |journal=PLOS ONE |date=2020 |volume=15 |issue=1…”

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<noinclude>{| 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" | '''预测条件'''
| style="border:none; text-align:right;" colspan="2" | 来源: <ref>
{{cite journal |last=Balayla |first=Jacques |title=流行阈值 (ϕe) 及筛查曲线的几何性质 |journal=PLOS ONE |date=2020 |volume=15 |issue=10 |pages=e0240215 |doi=10.1371/journal.pone.0240215 |pmid=33027310 |doi-access=free }}</ref><ref>
{{cite journal |last=Fawcett |first=Tom |title=ROC 分析简介 |journal=Pattern Recognition Letters |date=2006 |volume=27 |issue=8 |pages=861–874 |doi=10.1016/j.patrec.2005.10.010 |s2cid=2027090 |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=资产管理中数据分析：路面状况指数的成本效益预测|journal=Journal of Infrastructure Systems|volume=26|issue=1|pages=04019036|doi=10.1061/(ASCE)IS.1943-555X.0000512|s2cid=213782055 }}</ref><ref>
{{cite journal |first=David M. W. |last=Powers |date=2011 |title=评价：从精确度、召回率和F-度量到ROC、信息度和标记度与相关性 |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=机器学习百科全书 |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 联合预测验证研究工作组 |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=澳大利亚天气与气候研究合作|publisher=世界气象组织|access-date=2019-07-17}}</ref><ref>
{{cite journal |vauthors = Chicco D, Jurman G |title = 马修斯相关系数 (MCC) 在二元分类评估中优于 F1 分数和准确度的优势 |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 |doi-access = free }}</ref><ref>
{{cite journal |vauthors = Chicco D, Toetsch N, Jurman G |title = 马修斯相关系数 (MCC) 在两类混淆矩阵评估中比平衡精度、博彩信息度和标记度更可靠 |journal = BioData Mining |volume = 14 |issue = 13 |date = February 2021 |page = 13pmid = 33541410 | pmc = 7863449 |doi = 10.1186/s13040-021-00244-z |doi-access = free }}</ref><ref>
{{cite journal |author = Tharwat A. |title = 分类评估方法 |journal = Applied Computing and Informatics |date = August 2018 |volume = 17 |pages = 168–192 |doi = 10.1016/j.aci.2018.08.003 |doi-access = free }}</ref> {{navbar|Diagnostic testing diagram|plain=y}}
|-
| style="background:#eeeeee;" | [[Statistical population|总体人群]] = P + N
| style="background:#ccffff;" | '''预测阳性 (PP)'''
| style="background:#aadddd;" | '''预测阴性 (PN)'''
| style="border-left:double silver;" | [[Youden's_J_statistic|信息度]], {{small|博彩信息度 (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;|'''实际条件'''}}
| style="background:#ffffcc;" | '''阳性 (P)'''
| style="background:#ccffcc;" | '''[[True positive]] (TP), {{small|命中}}'''
| style="background:#ffdddd;" | '''[[False negative]] (FN), {{small|[[type II error]], 错失, 低估}}'''
| style="background:#eeffee;" | [[True positive rate]] (TPR), [[recall (information retrieval)|召回率]], [[Sensitivity (tests)|敏感性]] (SEN), {{small|检测概率, 命中率, [[statistical power|功效]]}} = {{sfrac|TP|P}} = 1 − FNR
| style="background:#ffeeee;" | [[False negative rate]] (FNR), {{small|错失率}} = {{sfrac|FN|P}} = 1 − TPR
|-
| style="background:#ddddaa;" | '''阴性 (N)'''
| style="background:#ffcccc;" | '''[[False positive]] (FP), {{small|[[type I error]], 虚警, 高估}}'''
| style="background:#bbeebb;" | '''[[True negative]] (TN), {{small|正确拒绝}}'''
| style="background:#eedddd;" | [[False positive rate]] (FPR), {{small|虚警概率, [[evaluation measures (information retrieval)#Fall-out|{{nowrap|降雨量}}]]}} = {{sfrac|FP|N}} = 1 − TNR
| style="background:#ddeedd;"| [[True negative rate]] (TNR), {{small|[[specificity (tests)|特异性]] (SPC), 选择性}} = {{sfrac|TN|N}} = 1 − FPR

|-
| style="border:none;" rowspan="3"|
| style="border-top:double silver; border-right:double silver;"|[[患病率]] = {{sfrac|P|P + N}}
| style="background:#eeffee;" | {{nowrap|[[阳性预测值]] (PPV),}} {{small|[[信息检索中的精确度|精确度]]}} = {{sfrac|TP|PP}} = 1 − FDR
| style="background:#ffeeee;border-right:double silver;"|[[漏报率]] (FOR) = {{sfrac|FN|PN}} = 1 − NPV
| style="background:#eeeeff;" | [[阳性似然比]] (LR+) = {{sfrac|TPR|FPR}}
| style="background:#eeeeff;" | [[阴性似然比]] (LR−) = {{sfrac|FNR|TNR}}
|-
| style="border-right:double silver;"|[[准确度与精确度#在二元分类中|准确度]] (ACC) = {{sfrac|TP + TN|P + N}}
| style="background:#eedddd;"|[[假发现率]] (FDR) = {{sfrac|FP|PP}} = 1 − PPV
| style="background:#ddeedd;"|[[阴性预测值]] (NPV) = {{sfrac|TN|PN}} = 1 − FOR
| style="border-top:double silver;border-right:double silver;" | [[标记度]] (MK), {{small|deltaP (Δp)}} = PPV + NPV − 1
| style="background:#eeeeff;" | [[诊断比值比|诊断{{nowrap|比值比}}]] (DOR) = {{sfrac|LR+|LR−}}
|-
| 平衡准确度 (BA) = {{sfrac|TPR + TNR|2}}
| style="border-top:double silver;"|[[F1 分数|F1 分数]] = {{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 指数]] (FM) = [math]\scriptstyle\mathsf\sqrt{\text{PPV}\times\text{TPR}}[/math]
| style="border-top:double silver;"|[[马修斯相关系数]] (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"|威胁分数 (TS), 关键成功指数 (CSI), [[Jaccard 指数#在二元分类混淆矩阵中的Jaccard指数|Jaccard 指数]] = {{sfrac|TP|TP + FN + FP}}
|}</noinclude>

模板:Diagnostic testing diagram - 版本历史

2024年1月25日 (四) 04:51 Zeroclanzhang

2024年1月25日 (四) 04:51 Zeroclanzhang