השוואת שיטות
סקרו את השיטות שבחרתם זו לצד זו; שורות שבהן יש הבדל מודגשות.
| דיוק מאוזן× | מטריצת בלבול× | מדד F1× | |
|---|---|---|---|
| תחום | הערכת מודלים | הערכת מודלים | הערכת מודלים |
| משפחה | MCDM | MCDM | MCDM |
| שנת המקור≠ | 2010 | 20th century | 1979 |
| הוגה השיטה≠ | Brodersen, Ong, Stephan, and Buhmann | Statistical foundations | C. J. van Rijsbergen |
| סוג≠ | Evaluation metric | Evaluation visualization | Evaluation metric |
| מקור מכונן≠ | 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 ↗ | van Rijsbergen, C. J. (1979). Information Retrieval (2nd ed.). Butterworth-Heinemann. link ↗ |
| כינויים | Average Recall, Equal-weight Average Sensitivity | Error Matrix, Contingency Table | F-measure, Harmonic Mean |
| קשורות | 5 | 5 | 5 |
| תקציר≠ | 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. | The F1-score is the harmonic mean of precision and recall, providing a single metric that balances both concerns. It was introduced by van Rijsbergen in information retrieval and has become a standard metric for evaluating classification models where both precision and recall are important. |
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