commercial data mining

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Commercial Data Mining
Author :
Publisher : Elsevier
Release Date :
ISBN 10 : 012416658X
Pages : 304 pages
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Whether you are brand new to data mining or working on your tenth predictive analytics project, Commercial Data Mining will be there for you as an accessible reference outlining the entire process and related themes. In this book, you'll learn that your organization does not need a huge volume of data or a Fortune 500 budget to generate business using existing information assets. Expert author David Nettleton guides you through the process from beginning to end and covers everything from business objectives to data sources, and selection to analysis and predictive modeling. Commercial Data Mining includes case studies and practical examples from Nettleton's more than 20 years of commercial experience. Real-world cases covering customer loyalty, cross-selling, and audience prediction in industries including insurance, banking, and media illustrate the concepts and techniques explained throughout the book. Illustrates cost-benefit evaluation of potential projects Includes vendor-agnostic advice on what to look for in off-the-shelf solutions as well as tips on building your own data mining tools Approachable reference can be read from cover to cover by readers of all experience levels Includes practical examples and case studies as well as actionable business insights from author's own experience

Commercial Data Mining

Whether you are brand new to data mining or working on your tenth predictive analytics project, Commercial Data Mining will be there for you as an accessible reference outlining the entire process and related themes. In this book, you'll learn that your organization does not need a huge volume of

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Data Mining with Rattle and R

Data mining is the art and science of intelligent data analysis. By building knowledge from information, data mining adds considerable value to the ever increasing stores of electronic data that abound today. In performing data mining many decisions need to be made regarding the choice of methodology, the choice of

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Commercial Data Mining of Criminal Justice System Records

Download or read online Commercial Data Mining of Criminal Justice System Records written by Criminal and Juvenile Justice Information Task Force (Minn.), published by Unknown which was released on 2008. Get Commercial Data Mining of Criminal Justice System Records Books now! Available in PDF, ePub and Kindle.

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Exploitation of Modern Heuristic Techniques Within a Commercial Data Mining Environment

Download or read online Exploitation of Modern Heuristic Techniques Within a Commercial Data Mining Environment written by J. C. W. Debuse, published by Unknown which was released on 1997. Get Exploitation of Modern Heuristic Techniques Within a Commercial Data Mining Environment Books now! Available in PDF, ePub and Kindle.

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Data Mining  Southeast Asia Edition

Our ability to generate and collect data has been increasing rapidly. Not only are all of our business, scientific, and government transactions now computerized, but the widespread use of digital cameras, publication tools, and bar codes also generate data. On the collection side, scanned text and image platforms, satellite remote

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Data Warehousing and Data Mining Techniques for Cyber Security

The application of data warehousing and data mining techniques to computer security is an important emerging area, as information processing and internet accessibility costs decline and more and more organizations become vulnerable to cyber attacks. These security breaches include attacks on single computers, computer networks, wireless networks, databases, or authentication

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Principles of Data Mining

This book explains and explores the principal techniques of Data Mining, the automatic extraction of implicit and potentially useful information from data, which is increasingly used in commercial, scientific and other application areas. It focuses on classification, association rule mining and clustering. Each topic is clearly explained, with a focus

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Introduction to Data Mining and Its Applications

This book explores the concepts of data mining and data warehousing, a promising and flourishing frontier in data base systems and new data base applications and is also designed to give a broad, yet in-depth overview of the field of data mining. Data mining is a multidisciplinary field, drawing work

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Monetising Data

Practical guide for deriving insight and commercial gain from data Monetising Data offers a practical guide for anyone working with commercial data but lacking deep knowledge of statistics or data mining. The authors — noted experts in the field — show how to generate extra benefit from data already collected and how

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Data Mining

Focusing on a data-centric perspective, this book provides a complete overview of data mining: its uses, methods, current technologies, commercial products, and future challenges. Three parts divide Data Mining: Part I describes technologies for data mining - database systems, warehousing, machine learning, visualization, decision support, statistics, parallel processing, and architectural

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Data Preparation for Data Mining

Data Preparation for Data Mining addresses an issue unfortunately ignored by most authorities on data mining: data preparation. Thanks largely to its perceived difficulty, data preparation has traditionally taken a backseat to the more alluring question of how best to extract meaningful knowledge. But without adequate preparation of your data,

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DATA MINING  The CRISP DM METHODOLOGY  The CLEM language and IBM SPSS MODELER

This book describes the CRISP-DM modelling process for data mining. SPSS (then ISL and now IBM-SPSS) had been providing Data Mining based services since 1990 and had launched the first commercial Data Mining tool Clementine in 1994. Now the principal product that implements the CRISP-DM Methodology is IBM SPSS Modeler. This book

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DATA MINING  Uses in Commercial Applications

Although neural networks are applied in a wide range of learning and commercial applications even though this method is not commonly used for data mining tasks. Companies have been collecting data for decades and have build up massive data warehouses and used data mining techniques to extract the value of

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Data Mining and Statistics for Decision Making

Data mining is the process of automatically searching large volumes of data for models and patterns using computational techniques from statistics, machine learning and information theory; it is the ideal tool for such an extraction of knowledge. Data mining is usually associated with a business or an organization's need to

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Data Mining Techniques and Applications

This concise and approachable introduction to data mining selects a mixture of data mining techniques originating from statistics, machine learning and databases, and presents them in an algorithmic approach. Aimed primarily at undergraduate readers, it presents not only the fundamental principles and concepts of the subject in an easy-to-understand way,

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