FPGrowth Example | Teradata Vantage - FPGrowth Example: Sports - 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
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rnn1580259159235.ditamap
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dita:id
B700-4003
lifecycle
previous
Product Category
Teradata Vantageā„¢

SQL Call

SELECT * FROM FPGrowth (
  ON sports AS InputTable
  OUT TABLE OutputRulesTable (fpgrowth_out_rule_1)
  OUT TABLE OutputPatternsTable (fpgrowth_out_pattern_1)
  USING
  TargetColumns ('sport')
  TransactionIDColumns ('player')
) AS dt; 

Output

SELECT CAST(pattern_sport AS VARCHAR(30)),
  length_of_pattern,
  "count",
  support
  
  FROM fpgrowth_out_pattern_1;
pattern_sport                   length_of_pattern                 count                 support
------------------------------  -----------------  --------------------  ----------------------
baseball,tennis                                 2                     1   7.14285714285714E-002
soccer,tennis                                   2                     2   1.42857142857143E-001
basketball,lacrosse                             2                     1   7.14285714285714E-002
soccer,track and field                          2                     3   2.14285714285714E-001
baseball,golf                                   2                     2   1.42857142857143E-001
baseball,basketball                             2                     4   2.85714285714286E-001
golf,lacrosse                                   2                     1   7.14285714285714E-002
basketball,golf                                 2                     1   7.14285714285714E-002
baseball,lacrosse                               2                     1   7.14285714285714E-002
baseball,soccer                                 2                     1   7.14285714285714E-002
soccer,basketball                               2                     1   7.14285714285714E-002
tennis,track and field                          2                     2   1.42857142857143E-001
lacrosse,rugby                                  2                     1   7.14285714285714E-002
golf,tennis                                     2                     2   1.42857142857143E-001
SELECT CAST(antecedent_sport AS VARCHAR(20)),
  CAST(consequence_sport AS VARCHAR(20)),
  count_of_antecedent,
  count_of_consequence,
  cntb,
  cnt_antecedent,
  cnt_consequence,
  score,
  support,
  confidence,
  lift,
  conviction,
  leverage,
  coverage,
  chi_square,
  z_score
  FROM fpgrowth_out_rule_1;
antecedent_sport      consequence_sport     count_of_antecedent  count_of_consequence                  cntb        cnt_antecedent       cnt_consequence                   score                 support              confidence                    lift              conviction                leverage                coverage              chi_square                 z_score
--------------------  --------------------  -------------------  --------------------  --------------------  --------------------  --------------------  ----------------------  ----------------------  ----------------------  ----------------------  ----------------------  ----------------------  ----------------------  ----------------------  ----------------------
baseball              basketball                              1                     1                     4                     5                     4   8.00000000000000E-001   2.85714285714286E-001   8.00000000000000E-001   2.80000000000000E 000   3.57142857142857E 000   1.83673469387755E-001   3.57142857142857E-001   1.00800000000000E 001                       ?
basketball            baseball                                1                     1                     4                     4                     5   8.00000000000000E-001   2.85714285714286E-001   1.00000000000000E 000   2.80000000000000E 000                       ?   1.83673469387755E-001   2.85714285714286E-001   1.00800000000000E 001                       ?