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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 |
|---|---|---|
| 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 |