Discovering Knowledge in Data: An Introduction to Data Mining - Hardcover

Larose, Daniel T.

Hardcover

ISBN 10: 0471666572 ISBN 13: 9780471666578

Verlag: John Wiley & Sons Inc, 2004

Inhaltsangabe

Learn Data Mining by doing data mining Data mining can be revolutionary--but only when ita 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: aeo Data preprocessing and classification aeo Exploratory analysis aeo Decision trees aeo Neural and Kohonen networks aeo Hierarchical and k--means clustering aeo Association rules aeo 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 Instructora s Manual presenting detailed solutions to all the problems in the book is available online.

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Über die Autorin bzw. den Autor

DANIEL T. LAROSE received his PhD in statistics from the University of Connecticut. An associate professor of statistics at Central Connecticut State University, he developed and directs Data Mining@CCSU, the worlda s first online master of science program in data mining. He has also worked as a data mining consultant for Connecticut--area companies. He is currently working on the next two books of his three--volume series on Data Mining: Data Mining Methods and Models and Data Mining the Web: Uncovering Patterns in Web Content, scheduled to publish respectively in 2005 and 2006.

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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.

Details zur Ausgabe

• Verlag: John Wiley & Sons Inc
• Erscheinungsdatum: 2004
• Sprache: Englisch
• ISBN 10: 0471666572
• ISBN 13: 9780471666578
• Einband: Tapa dura
• Anzahl der Seiten: 240
• Kontakt zum Hersteller: Nicht verfügbar
• Verantwortliche Person: Nicht verfügbar