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| Akurasi Seimbang× | Matriks Kebingungan× | |
|---|---|---|
| Bidang | Penilaian Model | Penilaian Model |
| Keluarga | MCDM | MCDM |
| Tahun asal≠ | 2010 | 20th century |
| Pengasas≠ | Brodersen, Ong, Stephan, and Buhmann | Statistical foundations |
| Jenis≠ | Evaluation metric | Evaluation visualization |
| Sumber perintis≠ | 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 ↗ | Everitt, B. S., & Hothorn, T. (2005). A Handbook of Statistical Analyses Using R. Chapman and Hall/CRC. link ↗ |
| Alias | Average Recall, Equal-weight Average Sensitivity | Error Matrix, Contingency Table |
| Berkaitan | 5 | 5 |
| Ringkasan≠ | 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. | The confusion matrix is a table that displays the counts of true positives, true negatives, false positives, and false negatives. It provides a complete picture of where a classifier makes correct and incorrect predictions, enabling calculation of all other classification metrics. |
| ScholarGateSet data ↗ |
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