Business Modeling and Data Mining (The Morgan Kaufmann Series in Data Management Systems)

Pyle, Dorian

ISBN 10: 155860653X / ISBN 13: 9781558606531

Verlag: Morgan Kaufmann, 2003

Beschreibung

Item in good condition and has highlighting/writing on text. Used texts may not contain supplemental items such as CDs, info-trac etc.

Bestandsnummer des Verkäufers 00030322510

Bibliografische Details

• Titel: Business Modeling and Data Mining (The Morgan Kaufmann Series in Data Management Systems)
• Verlag: Morgan Kaufmann
• Veröffentlichungsdatum: 2003
• Sprache: Englisch
• ISBN-10: 155860653X
• ISBN-13: 9781558606531
• Bindung: Softcover
• Zustand: Good

Über diesen Titel

Inhaltsangabe

Business Modeling and Data Mining demonstrates how real world business problems can be formulated so that data mining can answer them. The concepts and techniques presented in this book are the essential building blocks in understanding what models are and how they can be used practically to reveal hidden assumptions and needs, determine problems, discover data, determine costs, and explore the whole domain of the problem. This book articulately explains how to understand both the strategic and tactical aspects of any business problem, identify where the key leverage points are and determine where quantitative techniques of analysis -- such as data mining -- can yield most benefit. It addresses techniques for discovering how to turn colloquial expression and vague descriptions of a business problem first into qualitative models and then into well-defined quantitative models (using data mining) that can then be used to find a solution. The book completes the process by illustrating how these findings from data mining can be turned into strategic or tactical implementations.

Über die Autorin bzw. den Autor

Dorian Pyle is Chief Scientist and Founder of PTI (www.pti.com), which develops and markets PowerhouseT predictive and explanatory analytics software. Dorian has over 20 years experience in artificial intelligence and machine learning techniques which are used in what is known today as "data mining� or "predictive analytics�. He has applied this knowledge as a consultant with Knowledge Stream Partners, Xchange, Naviant, Thinking Machines, and Data Miners and with various companies directly involved in credit card marketing for banks and with manufacturing companies using industrial automation. In 1976 he was involved in building artificially intelligent machine learning systems utilizing the pioneering technologies that are currently known as neural computing and associative memories. He is current in and familiar with using the most advanced technologies in data mining including: entropic analysis (information theory), chaotic and fractal decomposition, neural technologies, evolution and genetic optimization, algebra evolvers, case-based reasoning, concept induction and other advanced statistical techniques.