Data Mining Methods and Applications Discrete Mathematics and Its Applications



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R3 101.00
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This excerpt is from "Data Mining Methods and Applications" by John R. Hunter. The book discusses data mining methods and applications and how they can be used to improve business intelligence. It also covers how to use data mining concepts in real-world scenarios.
Key Features
Discusses data mining methods and their applications
Discusses how to use data mining concepts in real-world scenarios
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Features
Author Stephan Kudyba , Kenneth Lawrence , Lawrence Lawrence
Format Hardcover
ISBN 9780849385223
Publisher Auerbach Publications
Manufacturer Auerbach Publications
Description

With today's information explosion, many organizations are now able to access a wealth of valuable data. Unfortunately, most of these organizations find they are ill-equipped to organize this information, let alone put it to work for them Gain a Competitive Advantage

  • Employ data mining in research and forecasting
  • Build models with data management tools and methodology optimization
  • Gain sophisticated breakdowns and complex analysis through multivariate, evolutionary, and neural net methods
  • Learn how to classify data and maintain quality
  • Transform Data into Business Acumen Data Mining Methods and Applications supplies organizations with the data management tools that will allow them to harness the critical facts and figures needed to improve their bottom line.

    Drawing from finance, marketing, economics, science, and healthcare, this forward thinking volume - Demonstrates how the transformation of data into business intelligence is an essential aspect of strategic decision-making Emphasizes the use of data mining concepts in real-world scenarios with large database components Focuses on data mining and forecasting methods in conducting market research



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