विधियों की तुलना करें
चुनी हुई विधियों की आमने-सामने समीक्षा करें; भिन्नता वाली पंक्तियाँ रेखांकित हैं।
| संतुलित सटीकता (Balanced Accuracy)× | सटीकता (Precision)× | |
|---|---|---|
| क्षेत्र | मॉडल मूल्यांकन | मॉडल मूल्यांकन |
| परिवार | MCDM | MCDM |
| उद्भव वर्ष≠ | 2010 | 20th century |
| प्रवर्तक≠ | Brodersen, Ong, Stephan, and Buhmann | Historical statistical foundations |
| प्रकार | Evaluation metric | Evaluation metric |
| मौलिक स्रोत≠ | 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 ↗ | Fawcett, T. (2006). An introduction to ROC analysis. Pattern Recognition Letters, 27(8), 861-874. DOI ↗ |
| उपनाम | Average Recall, Equal-weight Average Sensitivity | Positive Predictive Value, PPV |
| संबंधित | 5 | 5 |
| सारांश≠ | Balanced accuracy is the average of recall values computed for each class separately. It corrects for class imbalance by giving equal weight to the performance on each class, regardless of class frequency in the dataset. | Precision measures the proportion of positive predictions that were actually correct. It answers the question: 'Of all the cases we predicted as positive, how many were truly positive?' Precision is critical in scenarios where false positives are costly. |
| ScholarGateडेटासेट ↗ |
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