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Data mining techniques : for marketing, sales, and customer relationship management / Michael J.A. Berry, Gordon S. Linoff.

By: Contributor(s): Publication details: Indianapolis, Ind. : Wiley Pub., c2004.Edition: 2nd edDescription: xxv, 643 p. : ill. ; 24 cmISBN:
  • 9780471470649
  • 0471470643 (paper/website)
Subject(s): DDC classification:
  • 658.8/02 22
Contents:
Why and what is data mining? -- The virtuous cycle of data mining -- Data mining methodology and best practices -- Data mining applications in marketing and customer relationship management -- The lure of statistics: data mining using familiar tools -- Decision trees -- Artificial neural networks -- Nearest neighbor approaches : memory-based reasoning and collaborative filtering -- Market basket analysis and association rules -- Link analysis -- Automatic Cluster detection -- Knowing when to worry: hazard functions and survival analysis in marketing -- Genetic algorithms -- Data mining throughout the customer life cycle -- Data warehousing, OLAP, and data mining -- Building the data mining environment -- Preparing data for mining -- Putting data mining to work.
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Holdings
Item type Current library Home library Call number Copy number Status Date due Barcode Item holds
Book Book Ayesha Abed Library General Stacks Ayesha Abed Library General Stacks 658.802 BER (Browse shelf(Opens below)) 1 Available 3010021975
Total holds: 0

Includes index.

Why and what is data mining? -- The virtuous cycle of data mining -- Data mining methodology and best practices -- Data mining applications in marketing and customer relationship management -- The lure of statistics: data mining using familiar tools -- Decision trees -- Artificial neural networks -- Nearest neighbor approaches : memory-based reasoning and collaborative filtering -- Market basket analysis and association rules -- Link analysis -- Automatic Cluster detection -- Knowing when to worry: hazard functions and survival analysis in marketing -- Genetic algorithms -- Data mining throughout the customer life cycle -- Data warehousing, OLAP, and data mining -- Building the data mining environment -- Preparing data for mining -- Putting data mining to work.

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