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

By: Contributor(s): Indianapolis, Ind. : Wiley Pub., c2004Indianapolis, Ind. : Wiley Pub., c2004Edition: 2nd edDescription: xxv, 643 p. : ill. ; 24 cmISBN:
  • 0471470643 paper/website
Subject(s): DDC classification:
  • 658.802 B534 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.
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Holdings
Item type Current library Call number Status Date due Barcode
Print Materials Main Library General Circulation 658.802/B534 2004 (Browse shelf(Opens below)) Available 0095397

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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