KNIME Extension for Apache Spark core infrastructure version 4.3.3.v202104211345 by KNIME AG, Zurich, Switzerland
This node applies association rules created by a Spark rule learner*. The rules are applied to a given column with item sets (transactions). A rule matches an item set, if the item set contains all antecedent items of the rule. The consequent items of the matching rules are then added to the output set of predicted items if they are not already included in the input items collection (the output set contains only new items).
To avoid memory and computations explosions, the number of used association rules can be limited. A warning will be added to the node if the limit is reached and only the first n rules are used (this means randomly chosen on a unsorted set of rules).
The Spark Association Rule Learner Node can be used to generate the association rules. The Spark GroupBy or Spark SQL Node can be used to generate a collection of items as input.
Rules with missing values in the selected antecedent or consequent column and item rows with missing values in the selected item column are removed.
This node requires at least Apache Spark 2.0.
To use this node in KNIME, install KNIME Extension for Apache Spark from the following update site:
A zipped version of the software site can be downloaded here.
You don't know what to do with this link? Read our NodePit Product and Node Installation Guide that explains you in detail how to install nodes to your KNIME Analytics Platform.
You want to see the source code for this node? Click the following button and we’ll use our super-powers to find it for you.
Do you have feedback, questions, comments about NodePit, want to support this platform, or want your own nodes or workflows listed here as well? Do you think, the search results could be improved or something is missing? Then please get in touch! Alternatively, you can send us an email to firstname.lastname@example.org, follow @NodePit on Twitter, or chat on Gitter!
Please note that this is only about NodePit. We do not provide general support for KNIME — please use the KNIME forums instead.