Task: Market Basket Analysis, Evaluation (Pilot)

SUMMARY

Understanding which patterns are meaningful and actionable is essential for deriving value from frequent pattern-mining algorithms. This lesson focuses on evaluating the rules generated through measures like support, confidence, lift, and conviction, and aligns these metrics with business goals. You’ll also learn how to validate rules using real-world constraints and refine outputs to prioritize high-impact decisions. Whether you’re working in supply chain optimization, customer behavior analysis, or inventory planning, this lesson equips you with tools to ensure the quality and relevance of your insights.

In this lesson, you will perform the evaluation of association rules generated from a real life industrial dataset.

About The Author

Dilek Dustegor is a Professor of Computing Science at the University of Groningen in the Netherlands. She is interested in bridging the gaps between research, development and implementation using AI and automation. She is pursuing research about modeling, design and analysis of large scale / networked systems using IoT and ML techniques, with a special interest in smart city applications. She is a seasoned educator, and loves using the newest educational technologies for an enhanced learning experience.