Generate a table with synthetic scores (0.0 - 10.0), where a number of rows and column names for the table are provided by the user.
Use case: to create a table of possible scores then assign scores and use it to do the scoring, using several operators.
- learn from the table (createScoreCombiner) then apply using combineScores operator
- approximateLabelLook operator
- regular join
- Click + on the parent node.
- Enter the Generate Scores operator in the search field and select the operator from the Results to open the operator form.
- In the Table drop-down, enter or select the table containing the data to run this operator on.
- In the Number of Rows field, enter the number of rows to generate the scores.
- In the Column names, click Add More to add the list of column names to generate.
- Click Run to view the result.
- Click Save to add the operator to the playbook.
- Click Cancel to discard the operator form.
generateScores(table, numberOfRows, arrayOfColumnNames)
table: input table, not important, the operators requires a parent step, output is not correlated to input
numberOfRows: number of rows to produce
arrayOfColumnNames: column names example, ["score1", "score2", "score3"]
generateScores(lsof, 20, ["score1", "score2", "score3", "score4"]) --should create 20 rows and 4 columns in the arguments + lhub_score with no scores table where each row is distinct
Updated almost 2 years ago