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The non-negative, unbounded score that was calculated by the anomaly detection model.
This does not indicate how the value returned by the model for Score should be interpreted. Should higher scores be interpreted as anomalies, or scores closer to zero?
Document Details
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ID: 8b318bcc-48ff-eb63-9952-e811a283eb90
Version Independent ID: 1810a47c-da4c-8a3a-f5a0-61b31069f083
Confirmed here, Predictions that are anomalies will have higher scores than those that aren't anomalies.
What it is essentially computing is 1 minus the ratio of the length of the projected vector and the input vector. We expect the higher the scores the higher the chance of an anomaly because in case of no anomaly the data point should be able to be projected without changing the length much.
The Inputs and Output Columns section should have
PredictedLabel
in addition toScore
. Note: There is an issue with the current release of ML.NET wherePredictedLabel
always evaluates totrue
.Additionally, the description for
Score
reads:This does not indicate how the value returned by the model for
Score
should be interpreted. Should higher scores be interpreted as anomalies, or scores closer to zero?Document Details
⚠ Do not edit this section. It is required for docs.microsoft.com ➟ GitHub issue linking.
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