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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
(in positive samples)

estimated label
(predictive score > 50)


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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