This project focuses on applying popular clustering algorithms to analyze an air quality dataset. Through a series of tasks, we explore methods for clustering, evaluate their effectiveness, and interpret the results, using key metrics like Purity, SSE (Sum of Squared Error), and Silhouette Coefficients.
☆27Apr 14, 2025Updated last year
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