পদ্ধতির তুলনা করুন
নির্বাচিত পদ্ধতিগুলো পাশাপাশি পর্যালোচনা করুন; যে সারিগুলোয় পার্থক্য আছে সেগুলো চিহ্নিত করা হয়।
| Recall (Sensitivity)× | ভারসাম্যপূর্ণ নির্ভুলতা (Balanced Accuracy)× | নির্ভুলতা× | |
|---|---|---|---|
| ক্ষেত্র | মডেল মূল্যায়ন | মডেল মূল্যায়ন | মডেল মূল্যায়ন |
| পরিবার | MCDM | MCDM | MCDM |
| উদ্ভবের বছর≠ | 20th century | 2010 | 20th century |
| প্রবর্তক≠ | Historical statistical foundations | Brodersen, Ong, Stephan, and Buhmann | Historical statistical foundations |
| ধরন | Evaluation metric | Evaluation metric | Evaluation metric |
| মৌলিক উৎস≠ | Fawcett, T. (2006). An introduction to ROC analysis. Pattern Recognition Letters, 27(8), 861-874. 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 ↗ |
| অপর নাম≠ | Sensitivity, True Positive Rate, TPR | Average Recall, Equal-weight Average Sensitivity | Positive Predictive Value, PPV |
| সম্পর্কিত | 5 | 5 | 5 |
| সারসংক্ষেপ≠ | 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. | 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. |
| ScholarGateডেটাসেট ↗ |
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