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

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

Machine Learning Engine Analytic Function Reference

Product

Teradata Vantage

Release Number

9.02

9.01

2.0

1.3

Published

February 2022

Language

English (United States)

Last Update

2022-02-10

dita:mapPath

rnn1580259159235.ditamap

dita:ditavalPath

ybt1582220416951.ditaval

dita:id

B700-4003

lifecycle

Product Category

Teradata Vantage™

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

Input

attribution_sample_table
user_id	event	time_stamp
1	impression	2001-09-27 23:00:01
1	impression	2001-09-27 23:00:03
1	impression	2001-09-27 23:00:05
1	impression	2001-09-27 23:00:07
1	impression	2001-09-27 23:00:09
1	impression	2001-09-27 23:00:11
1	impression	2001-09-27 23:00:13
1	Email	2001-09-27 23:00:15
1	impression	2001-09-27 23:00:17
1	impression	2001-09-27 23:00:19
1	SocialNetwork	2001-09-27 23:00:20
1	Direct	2001-09-27 23:00:21
1	Referral	2001-09-27 23:00:22
1	PaidSearch	2001-09-27 23:00:23
2	impression	2001-09-27 23:00:29
2	impression	2001-09-27 23:00:31
2	impression	2001-09-27 23:00:33
2	impression	2001-09-27 23:00:36
2	impression	2001-09-27 23:00:38
2	impression	2001-09-27 23:00:43
2	impression	2001-09-27 23:00:47
2	OrganicSearch	2001-09-27 23:00:49
2	impression	2001-09-27 23:00:51

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', 'organicsearch:0.5:UNIFORM:NA',
          'direct:0.3:UNIFORM:NA', 'referral:0.2:UNIFORM:NA')
) 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 0.09000000357627869              -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  0.6000000238418579               -2.0
       1 referral      2001-09-27 23:00:22.000000  0.4000000059604645               -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.