MCDMClassification Metric
Tasakaalustatud täpsus
Tasakaalustatud täpsus on iga klassi jaoks eraldi arvutatud tundlikkusväärtuste keskmine. See korrigeerib klasside ebavõrdsust, andes igale klassile võrdse kaalu, sõltumata klassi esinemissagedusest andmestikus.
Loe meetodi täielikku kirjeldust
Ainult liikmetele
Logi sisseSelle osa lugemiseks logi sisse tasuta kontoga.
Method map
The neighbourhood of related methods — select a node to explore.
Allikad
- Brodersen, K. H., Ong, C. S., Stephan, K. E., & Buhmann, J. M. (2010). The balanced accuracy and its posterior distribution. 20th International Conference on Pattern Recognition (ICPR), 3121-3124. DOI: 10.1109/ICPR.2010.764 ↗
- Powers, D. M. (2011). Evaluation: From Precision, Recall and F-Measure to ROC, Informedness, Markedness and Correlation. Journal of Machine Learning Technologies, 2(1), 37-63. link ↗
Kuidas sellele lehele viidata
ScholarGate. (2026, June 3). Balanced Classification Accuracy. ScholarGate. https://scholargate.app/et/model-evaluation/balanced-accuracy
Which method?
Set this method beside its closest kin and read them side by side — the library lays the books on the table; the choice is yours.
- TäpsusMudelite hindamine↔ compare
- F1-hinneMudelite hindamine↔ compare
- Matthews' korrelatsioonikoefitsientMudelite hindamine↔ compare
- Tundlikkus (Recall)Mudelite hindamine↔ compare
- SpetsiifilisusMudelite hindamine↔ compare
Sellele viitavad
Märkasid sellel lehel viga? Teata sellest või paku parandust →