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Classifier Evaluation Metrics: Example
|
Actual Class\Predicted class |
cancer = yes |
cancer = no |
Total |
Recognition(%) |
|
|
cancer = yes |
90 |
210 |
300 |
30.00 ( sensitivity |
|
|
cancer = no |
140 |
9560 |
9700 |
98.56 ( specificity) |
|
|
Total |
230 |
9770 |
10000 |
96.40 ( accuracy ) |
Precision = 90/230 = 39.13% Recall = 90/300 = 30.00%
