مقایسهٔ روشها
روشهای انتخابی خود را کنار هم مرور کنید؛ ردیفهای متفاوت برجسته شدهاند.
| ضریب همبستگی متیوز (MCC)× | دقت موزون× | بازیابی (حساسیت)× | |
|---|---|---|---|
| حوزه | ارزیابی مدل | ارزیابی مدل | ارزیابی مدل |
| خانواده | MCDM | MCDM | MCDM |
| سال پیدایش≠ | 1975 | 2010 | 20th century |
| پدیدآور≠ | Brian W. Matthews | Brodersen, Ong, Stephan, and Buhmann | Historical statistical foundations |
| نوع | Evaluation metric | Evaluation metric | Evaluation metric |
| منبع بنیادین≠ | Matthews, B. W. (1975). Comparison of predicted and observed secondary structure of T4 phage lysozyme. Biochimica et Biophysica Acta (BBA)-Protein Structure, 405(2), 442-451. DOI ↗ | 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 ↗ |
| نامهای دیگر≠ | Phi Coefficient, Binary Classification Correlation | Average Recall, Equal-weight Average Sensitivity | Sensitivity, True Positive Rate, TPR |
| مرتبط | 5 | 5 | 5 |
| خلاصه≠ | The Matthews Correlation Coefficient (MCC) is a correlation measure between predicted and actual binary classifications. It ranges from -1 to 1 and is considered one of the most reliable single-score metrics for evaluating binary classifiers, especially on imbalanced datasets. | 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. | Recall measures the proportion of actual positive cases that were correctly identified by the classifier. It answers the question: 'Of all the cases that were truly positive, how many did we find?' Recall is critical in scenarios where missing positive cases is costly. |
| ScholarGateمجموعهداده ↗ |
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