Discovering Knowledge in Data

Learn Data Mining by doing Data mining can be revolutionary-but only when it's done right. The powerful black box data mining software now available can produce disastrously misleading results unless applied by a skilled and knowledgeable analyst. Discovering Knowledge in Data: An Introduction to Data Mining provides both the practical experience and the theoretical insight needed to reveal valuable information hidden in large data sets.Employing a "white box" methodology and with real-world case studies, this step-by-step guide walks readers through the various algorithms andstatistical structures that underlie the software and presents examples of their operation on actual large data sets. Principal topics include: Data preprocessing and classification Exploratory analysis Decision trees Neural and Kohonen networks Hierarchical and k-means clustering Association rules Model evaluation techniquesComplete with scores of screenshots and diagrams to encourage graphical learning, Discovering Knowledge in Data: An Introduction to Data Mining gives students in Business, Computer Science, and Statistics as well as professionals in the field the power to turn any data warehouse into actionable knowledge.