This visualization demonstrates association rule mining, showing how transactional data can be analyzed to identify item sets and their support values. The interface displays a transaction table, item set frequencies, and calculated support percentages, along with generated association rules that express confidence levels such as "if someone buys X, they are Y% likely to buy Z." The application uses AngularJS controllers and directives (ng-app, ng-controller, ng-repeat) to manage the interactive file upload and dynamically update the tables, while relying on JavaScript for the association rule algorithm and Bootstrap theming for styling.