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This article supports Audience Studio - Legacy. |
When you train Predictive Scoring, an evaluation runs in parallel to estimate the accuracy of prediction. The evaluation completes the following steps:
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Accuracy is the percentage of the “correct” estimated label computed over pairs of truth label and estimated label:
truth label | estimated label | |
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1 | 0 | Incorrect |
0 | 0 | Correct |
1 | 1 | Correct |
Because a rounded or truncated estimated label is less informative than a raw predictive score, Accuracy is not reliable as a metric. Therefore, we recommend that you consider the AUC (shorthand for ) which is a metric computed from raw predictive score.
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