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:




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