Topic 1 Question 81
A company has a binary classification model in production. An ML engineer needs to develop a new version of the model. The new model version must maximize correct predictions of positive labels and negative labels. The ML engineer must use a metric to recalibrate the model to meet these requirements. Which metric should the ML engineer use for the model recalibration?
Accuracy
Precision
Recall
Specificity
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コメント(4)
- 正解だと思う選択肢: A👍 1GiorgioGss2024/11/28
- 正解だと思う選択肢: A
Accuracy formula: (True Positives + True Negatives) / Total Predictions
👍 1GiorgioGss2024/11/28 - 正解だと思う選択肢: A
A. Accuracy: Correct choice; maximizes both true positives and true negatives. Formula: (TP + TN) / Total Predictions B. Precision: Focuses only on true positives, not negatives. Formula: TP / (TP + FP) C. Recall: Focuses on capturing all true positives, ignoring negatives. Formula: TP / (TP + FN) D. Specificity: Focuses only on true negatives, ignoring positives. Formula: TN / (TN + FP)
👍 1Saransundar2024/12/05
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