FPGrowth Syntax Elements - 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
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B700-4003
lifecycle
previous
Product Category
Teradata Vantageā„¢
OutputPatternsTable
[Required if PatternsOrRules is 'patterns' or 'both', disallowed otherwise.] Specify the name of the table where the function outputs the patterns.
OutputRulesTable
[Required if PatternsOrRules is 'patterns' or 'both', disallowed otherwise.] Specify the name of the table where the function outputs the rules.
TargetColumns
Specify the names of the InputTable columns that contain transaction items to analyze.
TransactionIDColumns
Specify the names of the InputTable columns that contain identifiers for the transaction items.
Do not specify the same column in both this syntax element and the GroupByColumns syntax element, because this causes incorrect counting in the partitions.
PatternsOrRules
[Optional] Specify whether the function outputs patterns, rules, or both. An example of a pattern is {onions, potatoes, hamburger}.
Default: 'both'
GroupByColumns
[Optional] Specify the names of InputTable columns that define the partitions into which the function groups the input data and calculates output for it. At least one column must be usable as a distribution key.
Do not specify the same column in both this syntax element and the TransactionIDColumns syntax element, because this causes incorrect counting in the partitions.
Default behavior: The function considers all input data to be in a single partition.
PatternDistributionKeyColumn
[Optional] Specify the name of the InputTable column to use as the distribution key for output_patterns_table.
Default: 'pattern_tranitemcolumns'.
RuleDistributionKeyColumn
[Optional] Specify the name of the InputTable column to use as the distribution key for output_rules_table.
Default: 'antecedent_tranitemcolumns'
CompressionLevel
[Optional] Specify the compression level the output tables.
Realized compression ratios depend on both this value and the data characteristics. These ratios typically range from 3x to 12x. For more information about compression, see the Teradata Database documentation.
Default: 'nocompress'
GroupSize
[Optional] Specify the number of transaction items to assign to each worker. This value must be an INTEGER in the range from 1 to the number of distinct transaction items, inclusive. For a machine with limited RAM, use a relatively small value.
Default: 4
MinSupport
[Optional] Specify the minimum support value of returned patterns (including the specified support value). This value must be a NUMERIC in the range [0, 1].
Default: 0.05
MinConfidence
[Optional] Specify the minimum confidence value of returned patterns (including the specified confidence value). This value must be a NUMERIC in the range [0, 1].
Default: 0.8
MaxPatternLength
[Optional] Specify the maximum length of returned patterns. The length of a pattern is the sum of the item numbers in the antecedent and consequence columns. This value must be an INTEGER greater than 2. MaxPatternLength also limits the length of returned rules to this value.
Default: 10
AntecedentCountRange
[Optional] Specify the range for na, the number of items in the antecedent. The function returns only patterns for which na is in the range [lower_bound, upper_bound]. The lower_bound must be greater an integer greater than 0. The lower_bound and upper_bound can be equal.
Default: '1-infinite'
ConsequenceCountRange
[Optional] Specify the range for nc, the number of items in the consequence. The function returns only patterns for which nc is in the range [lower_bound, upper_bound]. The lower_bound must be greater an integer greater than 0. The lower_bound and upper_bound can be equal.
Default: '1-1'
Delimiter
[Optional] Specify the delimiter that separates items in the output.
Default: ',' (comma)