Linganisha mbinu
Pitia mbinu ulizochagua bega kwa bega; safu zinazotofautiana zinaangaziwa.
| Usawa wa Usahihi (Balanced Accuracy)× | Matriki ya Kuchanganyikiwa× | |
|---|---|---|
| Nyanja | Tathmini ya Modeli | Tathmini ya Modeli |
| Familia | MCDM | MCDM |
| Mwaka wa asili≠ | 2010 | 20th century |
| Mwanzilishi≠ | Brodersen, Ong, Stephan, and Buhmann | Statistical foundations |
| Aina≠ | Evaluation metric | Evaluation visualization |
| Chanzo asilia≠ | 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 ↗ |
| Majina mbadala | Average Recall, Equal-weight Average Sensitivity | Error Matrix, Contingency Table |
| Zinazohusiana | 5 | 5 |
| Muhtasari≠ | 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. |
| ScholarGateSeti ya data ↗ |
|
|