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Data mining techniques : for marketing, sales, and customer relationship management

By: Berry, Michael J. A.
Contributor(s): Linoff, Gordon.
Material type: materialTypeLabelBookPublisher: Indianapolis, Ind. : Wiley Pub., ©2004Edition: 2nd ed.Description: xxv, 643 p. : ill. ; 24 cm.ISBN: 8126505176.Subject(s): Data mining | Marketing -- Data processing | Business -- Data processingOnline resources: Contributor biographical information | Table of contents | Publisher description
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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Item type Current location Collection Call number Status Date due Barcode Item holds
Books Books IIITD
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Computer Science and Engineering 006.3 BER-D (Browse shelf) Available G00065
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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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