Bandingkan metode
Tinjau metode pilihan Anda berdampingan; baris yang berbeda akan disorot.
| Matriks Kebingungan× | Presisi× | |
|---|---|---|
| Bidang | Evaluasi Model | Evaluasi Model |
| Keluarga | MCDM | MCDM |
| Tahun asal | 20th century | 20th century |
| Pencetus≠ | Statistical foundations | Historical statistical foundations |
| Tipe≠ | Evaluation visualization | Evaluation metric |
| Sumber perintis≠ | Everitt, B. S., & Hothorn, T. (2005). A Handbook of Statistical Analyses Using R. Chapman and Hall/CRC. link ↗ | Fawcett, T. (2006). An introduction to ROC analysis. Pattern Recognition Letters, 27(8), 861-874. DOI ↗ |
| Alias | Error Matrix, Contingency Table | Positive Predictive Value, PPV |
| Terkait | 5 | 5 |
| Ringkasan≠ | 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. | 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. |
| ScholarGateSet data ↗ |
|
|