SAP HANA Predictive Analysis Library (PAL)

PAL_FPGROWTH_VALUES_TBL:
3.4.3 K-Optimal Rule Discovery (KORD)
K-optimal rule discovery (KORD) follows the idea of generating association rules with respect to a well-defined
measure, instead of first finding all frequent itemsets and then generating all possible rules. The algorithm only
calculates the top-k rules according to that measure. The size of the right hand side (RHS) of those rules is
restricted to one. Futhermore, the KORD implementation generates only non-redundant rules.
The algorithm's search strategy is based on the so-called OPUS search. While the search space of all possible
LHSs is traversed in a depth-first manner, the information about all qualified RHSs of the rules for a given LHS
is propagated further to the deeper search levels. KORD does not build a real tree search structure; instead it
traverses the LHSs in a specific order, which allows the pruning of the search space by simply not visiting
those itemsets subsequently. In this way it is possible to use pruning rules which restrict the possible LHSs
and RHSs at different rule generation stages.
Prerequisites
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There are no duplicated items in each transaction.
The input data does not contain null value. The algorithm will issue errors when encountering null values.
KORD
Procedure Generation
CALL SYS.AFLLANG_WRAPPER_PROCEDURE_CREATE(‘AFLPAL’, ‘KORD’, ‘’,
'', );
The signature table should contain the following records:
Table 240:
Position Schema Name Table Type Name Parameter Type
1
IN
SAP HANA Predictive Analysis Library (PAL)
PAL Functions P U B L I C 315