Data Mining: Practical Machine Learning Tools and Techniques aims to demystify data mining and machine-learning: presenting a practical, hands-on guide to extracting meaningful information from raw data using established algorithms, statistical and machine-learning techniques, and tool-supported workflows. The book combines theory and practice: it explains the core concepts underpinning classification, regression, clustering, association rules, model evaluation, data preprocessing, and more but also shows how to implement them in real-world settings using the accompanying software toolkit (WEKA).