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supervisedScorer combine tables using autojoin operator by selecting distinct rows. You can manually assign scores for 2 rows and update the table, the rest of the rows will be updated with the final score automatically.
For example, if the predictor assigns a score of 6 but in the rules, we assigned 9, the final result will be 9.

Operator Usage in Easy Mode

1. Click + on the parent node.
2. Enter the Supervised Scorer operator in the search field and select the operator from the Results to open the operator form.
3. In the Table drop-down, enter or select a table to apply the operator.
4. Click Run to view the result.
5. Click Save to add the operator to the playbook.
6. Click Cancel to discard the operator form.

Usage Details

LQL Command

supervisedScorer(tables:TableReference[])

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Output
A scored table where each row is scored based on the model that was learned from all previous manually assigned scores. It will return lhub_score, mindistToRule (closest distance to ruleset), isFromRuleset (boolean), and score columns from tables.

Example

InputTable = userScore

InputTable = ipScore

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