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MCDMClassification Metric

Uravnotežena tačnost

Uravnotežena tačnost je prosečna vrednost mera odziva (recall) izračunatih odvojeno za svaku klasu. Ona korigira klasnu neuravnoteženost dajući jednaku težinu učinku na svakoj klasi, bez obzira na učestalost klase u skupu podataka.

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Method map

The neighbourhood of related methods — select a node to explore.

Izvori

  1. 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
  2. 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

Kako citirati ovu stranicu

ScholarGate. (2026, June 3). Balanced Classification Accuracy. ScholarGate. https://scholargate.app/sr/model-evaluation/balanced-accuracy

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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.

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Citirana u

ScholarGateBalanced Accuracy (Balanced Classification Accuracy). Preuzeto 2026-06-15 sa https://scholargate.app/sr/model-evaluation/balanced-accuracy · Skup podataka: https://doi.org/10.5281/zenodo.20539026