HANA AprioriLite

Properties that can be configured for the HANA AprioriLite algorithm.

Syntax Use this algorithm to find frequent itemset patterns in large transactional datasets to generate association rules. Apriori Lite also supports sampling within the algorithm.
Note
  • You can use HANA AprioriLite from within HANA Apriori algorithm properties by selecting AprioriLite as the Apriori Type.
  • Creating models using the HANA AprioriLite algorithm is not supported.
  • It only calculates two large itemsets.
HANA AprioriLite Properties
Table 1: Algorithm Properties
Property Description
Apriori Type Click AprioriLite.
Item Column Select the columns containing the items to which you want to apply the algorithm.
TransactionID Column Select the column containing the transaction IDs to which you want to apply the algorithm.
Missing Values Select the method for handling missing values.
Possible methods:
  • Ignore: The algorithm skips the records containing missing values in the independent or dependent columns.
  • Keep: The algorithm retains missing values for processing.
Support Enter a value for the minimum support of an item. The default value is 0.1.
Confidence Enter a value for the minimum confidence of rules/association. The default value is 0.8.
Sampling Required Select this option if you want to sample the data.
Sampling Percentage Enter the sampling percentage.
Recalculation Required Select this option if you want to recalculate the support and confidence in each iteration.
Number of Threads Enter the number of threads to be used for execution.