MCDMClassification Metric
Usahihi
Usahihi ni uwiano wa utabiri sahihi kati ya jumla ya utabiri uliofanywa na modeli ya uainishaji. Ni kipimo cha utendaji kinachoeleweka zaidi na hupima mara ngapi kiainishaji hufanya utabiri sahihi kwa ujumla, bila kujali darasa.
Soma mbinu kamili
Kwa wanachama pekee
IngiaIngia kwa akaunti ya bure ili kusoma sehemu hii.
Method map
The neighbourhood of related methods — select a node to explore.
Vyanzo
- Fawcett, T. (2006). An introduction to ROC analysis. Pattern Recognition Letters, 27(8), 861-874. DOI: 10.1016/j.patrec.2005.10.010 ↗
- 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 ↗
Jinsi ya kunukuu ukurasa huu
ScholarGate. (2026, June 3). Classification Accuracy. ScholarGate. https://scholargate.app/sw/model-evaluation/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.
- Usawa wa Usahihi (Balanced Accuracy)Tathmini ya Modeli↔ compare
- Matriki ya KuchanganyikiwaTathmini ya Modeli↔ compare
- F1-ScoreTathmini ya Modeli↔ compare
- UsahihiTathmini ya Modeli↔ compare
- Kumbukumbu (Usikivu)Tathmini ya Modeli↔ compare
Imerejelewa na
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