Attribution_MLE Example (Single Input): Dynamic Weighted Distribution Models - Teradata Vantage

Machine Learning Engine Analytic Function Reference

Product
Teradata Vantage
Release Number
8.10
1.1
Published
October 2019
Language
English (United States)
Last Update
2019-12-31
dita:mapPath
ima1540829771750.ditamap
dita:ditavalPath
jsj1481748799576.ditaval
dita:id
B700-4003
lifecycle
previous
Product Category
Teradata Vantageā„¢

This example uses the single-input Attribution_MLE function.

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:WEIGHTED:0.4,0.3,0.2,0.1')
  SecondModel ('EVENT_OPTIONAL', 'ALL:1:WEIGHTED:0.4,0.3,0.2,0.1')
) AS dt ORDER BY 1, 3;

Output

 user_id event         time_stamp                 attribution         time_to_conversion 
 ------- ------------- -------------------------- ------------------- ------------------ 
       1 impression    2001-09-27 23:00:01.000000                 0.0               NULL
       1 impression    2001-09-27 23:00:03.000000                 0.0               NULL
       1 impression    2001-09-27 23:00:05.000000                 0.0               NULL
       1 impression    2001-09-27 23:00:07.000000                 0.0               NULL
       1 impression    2001-09-27 23:00:09.000000                 0.0               NULL
       1 impression    2001-09-27 23:00:11.000000 0.08100000023841858               -9.0
       1 impression    2001-09-27 23:00:13.000000 0.16200000047683716               -7.0
       1 email         2001-09-27 23:00:15.000000  0.1899999976158142               -5.0
       1 impression    2001-09-27 23:00:17.000000 0.24300000071525574               -3.0
       1 impression    2001-09-27 23:00:19.000000  0.3240000009536743               -1.0
       1 socialnetwork 2001-09-27 23:00:20.000000                NULL               NULL
       1 direct        2001-09-27 23:00:21.000000  0.4285714328289032               -2.0
       1 referral      2001-09-27 23:00:22.000000  0.5714285969734192               -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                 0.0               NULL
       2 impression    2001-09-27 23:00:47.000000 0.10000000149011612              -12.0
       2 impression    2001-09-27 23:00:51.000000 0.20000000298023224               -8.0
       2 impression    2001-09-27 23:00:53.000000 0.30000001192092896               -6.0
       2 impression    2001-09-27 23:00:55.000000  0.4000000059604645               -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.