পদ্ধতির তুলনা করুন
নির্বাচিত পদ্ধতিগুলো পাশাপাশি পর্যালোচনা করুন; যে সারিগুলোয় পার্থক্য আছে সেগুলো চিহ্নিত করা হয়।
| ম্যাথিউস কোরিলেশন কোএফিসিয়েন্ট (MCC)× | নির্ভুলতা× | Recall (Sensitivity)× | |
|---|---|---|---|
| ক্ষেত্র | মডেল মূল্যায়ন | মডেল মূল্যায়ন | মডেল মূল্যায়ন |
| পরিবার | MCDM | MCDM | MCDM |
| উদ্ভবের বছর≠ | 1975 | 20th century | 20th century |
| প্রবর্তক≠ | Brian W. Matthews | Historical statistical foundations | Historical statistical foundations |
| ধরন | Evaluation metric | Evaluation metric | Evaluation metric |
| মৌলিক উৎস≠ | 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 ↗ | Fawcett, T. (2006). An introduction to ROC analysis. Pattern Recognition Letters, 27(8), 861-874. DOI ↗ |
| অপর নাম≠ | Phi Coefficient, Binary Classification Correlation | Positive Predictive Value, PPV | Sensitivity, True Positive Rate, TPR |
| সম্পর্কিত | 5 | 5 | 5 |
| সারসংক্ষেপ≠ | 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. | 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. |
| ScholarGateডেটাসেট ↗ |
|
|
|