Solving Association Problems in Rulex

Association problems aim to retrieve rules that can identify relations between variables associated with the same identifier (e.g. a supermarket customer).

The output can be a set of frequent itemsets or actual association rules.

Rulex Association Tasks

Rulex provides the following tasks to solve association problems:

Task	Description	Link

Task	Description	Link
Anomaly Detection	Extracts and characterizes anomalies from an event log, singling out the events in the flow which do not fit with any of the frequent sequences in the process model.	Using Anomaly Detection to Solve Association Problems
Assortment Optimizer	Extracts and generates replacement rules from frequent itemsets.	Using Assortment Optimizer to Solve Association Problems
Frequent Itemsets Mining	Extracts recurrent item associations from a dataset.	Using Frequent Itemsets Mining to Solve Association Problems
Hierarchical Basket Analysis	Generates association rules from frequent itemsets.	Using Hierarchical Basket Analysis to Solve Association Problems
Sequence Analysis	Extracts frequent sequences from event logs.	Using Sequence Analysis to Solve Association Problems
Similar Items Detector	Generates description-based and sales-based replacement rules.	Using Similar Items Detector to Solve Association Problems