Which of the following evaluation metrics can be used to evaluate a model with categorical output variable with exactly two categories? (check all that apply) ☐ specificity (true negative rate) ☐ accuracy (proportion of correctly predicted outputs) deviance O AUC and ROC ☐ false positive rate root mean squared error ☐ sensitivity (true positive rate, recall) ☐ cross-entropy
Which of the following evaluation metrics can be used to evaluate a model with categorical output variable with exactly two categories? (check all that apply) ☐ specificity (true negative rate) ☐ accuracy (proportion of correctly predicted outputs) deviance O AUC and ROC ☐ false positive rate root mean squared error ☐ sensitivity (true positive rate, recall) ☐ cross-entropy
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![Which of the following evaluation metrics can be used to evaluate a model with categorical
output variable with exactly two categories? (check all that apply)
☐ specificity (true negative rate)
☐ accuracy (proportion of correctly predicted outputs)
deviance
O AUC and ROC
☐ false positive rate
root mean squared error
☐ sensitivity (true positive rate, recall)
☐ cross-entropy](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2Fe99fe633-2e82-4dde-a878-82e2251a369a%2F98d13808-7f22-417b-b9c2-65184387b0c4%2Fdejx2i_processed.jpeg&w=3840&q=75)
Transcribed Image Text:Which of the following evaluation metrics can be used to evaluate a model with categorical
output variable with exactly two categories? (check all that apply)
☐ specificity (true negative rate)
☐ accuracy (proportion of correctly predicted outputs)
deviance
O AUC and ROC
☐ false positive rate
root mean squared error
☐ sensitivity (true positive rate, recall)
☐ cross-entropy
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