A Practical Guide to Data Mining for Business and Industry

  • 4h 43m
  • Andrea Ahlemeyer-Stubbe, Shirley Coleman
  • John Wiley & Sons (UK)
  • 2014

Data mining is well on its way to becoming a recognized discipline in the overlapping areas of IT, statistics, machine learning, and AI. Practical Data Mining for Business presents a user-friendly approach to data mining methods, covering the typical uses to which it is applied. The methodology is complemented by case studies to create a versatile reference book, allowing readers to look for specific methods as well as for specific applications. The book is formatted to allow statisticians, computer scientists, and economists to cross-reference from a particular application or method to sectors of interest.

In this Book

  • Glossary of Terms
  • Introduction
  • Data Mining Definition
  • All about Data
  • Data Preparation
  • Analytics
  • Methods
  • Validation and Application
  • Marketing—Prediction
  • Intra-Customer Analysis
  • Learning from a Small Testing Sample and Prediction
  • Miscellaneous
  • Software and Tools—A Quick Guide
  • Overviews
  • Bibliography
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