1.1 - 8.10 - Attribution_MLE Example (Single Input): Multiple Regular Models, One Optional Model - Teradata Vantage

Teradata Vantage™ - Machine Learning Engine Analytic Function Reference

Product
Teradata Vantage
Release Number
1.1
8.10
Release Date
October 2019
Content Type
Programming Reference
Publication ID
B700-4003-079K
Language
English (United States)

Using the single-input Attribution_MLE function, this example specifies one distribution model for each type of regular event and one distribution model for optional events.

SQL Call

SELECT * FROM Attribution_MLE (
  ON attribution_sample_table PARTITION BY user_id
    ORDER BY time_stamp
  USING
  EventColumn ('event')
  ConversionEvents ('socialnetwork', 'paidsearch')
  OptionalEvents ('organicsearch', 'direct', 'referral')
  TimeColumn ('time_stamp')
  WindowSize ('rows:10&seconds:20')
  FirstModel ('EVENT_REGULAR', 'email:0.19:LAST_CLICK:NA',
          'impression:0.81:UNIFORM:NA')
  SecondModel ('EVENT_OPTIONAL', 'ALL:1:EXPONENTIAL:0.5,ROW')
) AS dt ORDER BY 1, 3;

Output

The only difference between this output and the output of Attribution_MLE Example (Single Input): One Regular Model, Multiple Optional Models is the attribution of the optional events.

 user_id event         time_stamp                 attribution         time_to_conversion 
 ------- ------------- -------------------------- ------------------- ------------------ 
       1 impression    2001-09-27 23:00:01.000000 0.09000000357627869              -19.0
       1 impression    2001-09-27 23:00:03.000000 0.09000000357627869              -17.0
       1 impression    2001-09-27 23:00:05.000000 0.09000000357627869              -15.0
       1 impression    2001-09-27 23:00:07.000000 0.09000000357627869              -13.0
       1 impression    2001-09-27 23:00:09.000000 0.09000000357627869              -11.0
       1 impression    2001-09-27 23:00:11.000000 0.09000000357627869               -9.0
       1 impression    2001-09-27 23:00:13.000000 0.09000000357627869               -7.0
       1 email         2001-09-27 23:00:15.000000  0.1899999976158142               -5.0
       1 impression    2001-09-27 23:00:17.000000 0.09000000357627869               -3.0
       1 impression    2001-09-27 23:00:19.000000 0.09000000357627869               -1.0
       1 socialnetwork 2001-09-27 23:00:20.000000                NULL               NULL
       1 direct        2001-09-27 23:00:21.000000  0.3333333432674408               -2.0
       1 referral      2001-09-27 23:00:22.000000  0.6666666865348816               -1.0
       1 paidsearch    2001-09-27 23:00:23.000000                NULL               NULL
       2 impression    2001-09-27 23:00:29.000000                 0.0               NULL
       2 impression    2001-09-27 23:00:31.000000                 0.0               NULL
       2 impression    2001-09-27 23:00:33.000000                 0.0               NULL
       2 impression    2001-09-27 23:00:36.000000                 0.0               NULL
       2 impression    2001-09-27 23:00:38.000000                 0.0               NULL
       2 impression    2001-09-27 23:00:43.000000 0.20000000298023224              -16.0
       2 impression    2001-09-27 23:00:47.000000 0.20000000298023224              -12.0
       2 impression    2001-09-27 23:00:51.000000 0.20000000298023224               -8.0
       2 impression    2001-09-27 23:00:53.000000 0.20000000298023224               -6.0
       2 impression    2001-09-27 23:00:55.000000 0.20000000298023224               -4.0
       2 socialnetwork 2001-09-27 23:00:59.000000                NULL               NULL

Download a zip file of all examples and a SQL script file that creates their input tables from the attachment in the left sidebar.