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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 cmContent type:
  • text
Media type:
  • unmediated
Carrier type:
  • volume
ISBN:
  • 0471470643
Subject(s): LOC classification:
  • HF5415.125 .B47 2004
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.
Holdings
Item type Current library Home library Shelving location Call number Materials specified Status Barcode
Books Books American University in Dubai American University in Dubai Main Collection HF 5415.125 .B47 2004 (Browse shelf(Opens below)) Copy Type:01 - Books Available 250125

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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