UA 2026 - Data Mining

A portfolio of four hands-on assignments completed for the Data Mining course at the University of Antwerp, each tackling a distinct pillar of the field: pattern discovery, recommendation, unsupervised structure detection, and supervised classification. Together they span the full data mining pipeline from raw transactional and textual data through model building, evaluation, and interpretation, with each project isolated in its own submodule for clarity and reproducibility.

Projects

• Frequent Pattern Mining: Association rule mining (Apriori) on an online grocery retailer’s transactional data to uncover product-category and purchase-timing insights.
• Recommender Systems: Collaborative filtering and hybrid recommendation models built and evaluated on a movie ratings dataset.
• Clustering and Anomaly Detection: Recovering topic groups from 2164 unlabeled text documents via clustering, and flagging 50 anomalous documents from an unsafe website.
• Classification: Decision Tree and Random Forest classifiers on census income data, with feature selection comparisons and SHAP-based explainability.