পদ্ধতির তুলনা করুন
নির্বাচিত পদ্ধতিগুলো পাশাপাশি পর্যালোচনা করুন; যে সারিগুলোয় পার্থক্য আছে সেগুলো চিহ্নিত করা হয়।
| নির্দিষ্টতা (Specificity)× | ভারসাম্যপূর্ণ নির্ভুলতা (Balanced Accuracy)× | ম্যাথিউস কোরিলেশন কোএফিসিয়েন্ট (MCC)× | নির্ভুলতা× | |
|---|---|---|---|---|
| ক্ষেত্র | মডেল মূল্যায়ন | মডেল মূল্যায়ন | মডেল মূল্যায়ন | মডেল মূল্যায়ন |
| পরিবার | MCDM | MCDM | MCDM | MCDM |
| উদ্ভবের বছর≠ | 20th century | 2010 | 1975 | 20th century |
| প্রবর্তক≠ | Historical statistical foundations | Brodersen, Ong, Stephan, and Buhmann | Brian W. Matthews | Historical statistical foundations |
| ধরন | Evaluation metric | 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 ↗ | 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 ↗ | Fawcett, T. (2006). An introduction to ROC analysis. Pattern Recognition Letters, 27(8), 861-874. DOI ↗ |
| অপর নাম | True Negative Rate, TNR | Average Recall, Equal-weight Average Sensitivity | Phi Coefficient, Binary Classification Correlation | Positive Predictive Value, PPV |
| সম্পর্কিত | 5 | 5 | 5 | 5 |
| সারসংক্ষেপ≠ | Specificity measures the proportion of actual negative cases that were correctly identified as negative by the classifier. It answers the question: 'Of all the cases that were truly negative, how many did we correctly reject?' Specificity is complementary to recall and is essential when false positives are 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. | 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. | 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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