Business Modeling and Data Mining

Author:   Dorian Pyle
Publisher:   Elsevier Science & Technology
ISBN:  

9781558606531


Pages:   650
Publication Date:   17 May 2003
Format:   Paperback
Availability:   In Print   Availability explained
Limited stock is available. It will be ordered for you and shipped pending supplier's limited stock.

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Business Modeling and Data Mining


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Full Product Details

Author:   Dorian Pyle
Publisher:   Elsevier Science & Technology
Imprint:   Morgan Kaufmann Publishers In
Dimensions:   Width: 18.70cm , Height: 3.70cm , Length: 23.50cm
Weight:   1.180kg
ISBN:  

9781558606531


ISBN 10:   155860653
Pages:   650
Publication Date:   17 May 2003
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Paperback
Publisher's Status:   Out of Print
Availability:   In Print   Availability explained
Limited stock is available. It will be ordered for you and shipped pending supplier's limited stock.

Table of Contents

Part I: A Map of the Territory: The World, Knowledge and Models. Translating Experience. Modeling and Mining: Putting It Together. Part II: Business Modeling: What is a Model? Framing Business Models. Getting the Right Model. Getting the Model Right. Deploying the Model. Part III: Data Mining: Getting Started. What Mining Tools Do. Getting the Initial Model: Basic Practices of Data Mining. Improving the Mined Model. Deploying the Mined Model. Part IV: Methodology: Methodology. Resources.

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Author Information

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.

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