Clustering, Association, and Frequent Pattern Mining

As part of a research project for CS 432: Introduction to Data Mining, I wrote a detailed report on data analysis of a drug consumption-related dataset. The report focused on the various factors affecting drug consumption in Connecticut, USA. State-of-the-art algorithms for clustering like DBSCAN, Apriori, and Fpgrowth for Association and Frequent Pattern Mining were employed to make data-driven inferences regarding drug consumption in Connecticut, USA. PDF Link