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Scores the events on the specified groupByField and metricField in the given table, same as the original BaselineScorer, along with some new mutable parameters. The higher score the more abnormal event is.

Operator Usage in Easy Mode

  1. Click + on the parent node.
  2. Enter the Baseline Scorer operator in the search field and select the operator from the Results to open the operator form.
  3. In the Input Table drop-down, enter or select the table containing the data to run this operator on.
  4. In the Group By Field, enter the column name by which to group the rows by.
  5. In the Metric Field, enter the column name that contains the metric to be used for scoring.
  6. In the Baseline Table drop-down, enter or select the name of the baseline table.
  7. In the Not In Baseline Score field, enter the score for items not in the baseline. Default is 8.
  8. In the Not Enough Examples Score field, enter the score for items less in number than the notEnoughExamplesThreshold. Default is 6.
  9. In the Not Enough Examples Threshold field, enter the threshold for similar items. Default is 1.
  10. In the Max Std Dev field, enter the maximum value for standard deviation. Default is 10.0.
  11. In the Std Dev Multiplier field, enter the multiplier for standard deviation. Default is 1.0.
  12. In the Min Ratio Between Std Dev And Avg field, enter the minimum Ratio between mean and standard deviation. Default is 0.3.
  13. Click Run to view the result.
  14. Click Save to add the operator to the playbook.
  15. Click Cancel to discard the operator form.

Usage Details

LQL Command

baselineScorerV2(inputTable, groupByField, metricField, baselineTable, notInBaselineScore,
                 notEnoughExamplesScore, notEnoughExamplesThreshold, maxStdDev, stdDevMultiplier,
                 minRatioBetweenStdDevAndAvg)

** Input**
inputTable (TableReference) - The table containing the data to run this operator on.
groupByField (ColumnReference) - The column by which to group the rows by
metricField (ColumnReference) - The column that contains the metric to be used for scoring
baselineTable (TableReference) - The name of the baseline table
notInBaselineScore (Long): Score for items not in baseline. Default is 8
notEnoughExamplesScore (Long) - Score for items less in number than the notEnoughExamplesThreshold. Default is 6
notEnoughExamplesThreshold (Long) - Threshold for similar items. Default is 1
maxStdDev (Double) - Maximum value for standard deviation. Default is 10.0
stdDevMultiplier (Double) - Multiplier for standard deviation. Default is 1.0
minRatioBetweenStdDevAndAvg (Double) - Minimum Ratio between mean and standard deviation. Default is 0.3

Output
The input table with an additional lhub_score column containing the score.

Example

Input
tableA:

id user download_count
x1 emil 12
x2 emil 22
x3 monica 32
x4 monica 35

tableB:

id user download_count
v1 monica 25
v2 emil 15
v3 emil 50

LQL Command

baselineScorerV2(tableB, "user", "download_count", tableA , 8 , 6 , 1 , 10.0 , 1.0 , 0.3)

Output

id user download_count lhub_score lh_baseline lhub_confidence_score
v3 emil 50 4 12,22 4
v1 monica 25 0 32,35 4
v2 emill 15 0 12,22 4
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