baselineScorerV2

[ 1 Operator usage in easy mode ] [ 2 Usage details ] [ 3 Example ]

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

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

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

tableB:

id	user	download_count

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

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