Data Mining

Catalog description

Algorithmic and practical aspects of dis - covering patterns and relationships in large databases. Hands-on expe- rience in data analysis, clustering and prediction. Data preprocessing and exploration, data warehousing, association rule mining, classifica - tion and regression, clustering, anomaly detection, human factors and social issues in data mining.