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Given a table with multiple scores, assume that a final score was created by combining those scores. Using that final score, create a model that can estimate final scores for other tables (train model).

Example uses for this operator
Assume you have 1 million events with multiple scores and you want to assign final scores for all of them without manually annotating each event. This operator allows you to annotate a subsample of the data (say 100 events) and use that knowledge to score the remaining 99.9%.

•  This operator creates the model for combining scores. Use the combineScores operator to combine scores using the model that you create with this operator.

Trained models are not displayed in the UI, so remember the name of the model that was created.

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Example

Input
table = github_logs

LQL command

createScoreCombiner(table, "downloadAndLoginScorer", "finalScore", "downloadScore", "loginScore")

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