Title: Discovering knowledge in data
First published: 2005
Description: Learn Data Mining by doing data mining  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 and statistical 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 techniques  Complete 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.    An Instructor's Manual presenting detailed solutions to all the problems in the book is available online.
Subjects: Data mining, Computer Technology, Nonfiction, Exploration de données (informatique), Information storage and retrieval, Information systems, Qa76.9.d343 l38 2005, 006.3/12
LC classification: QA76.9.D343 L38 2005