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

Yazar: Katkıda bulunan(lar):Materyal türü: MetinMetinDil: İngilizce Yayın ayrıntıları:Indianapolis : Wiley, 2004.Baskı: 2nd edTanım: xxv, 643 p. : ill., 1 map ; 24 cmISBN:
  • 0471470643
Konu(lar): DDC sınıflandırma:
  • 658.8/02
LOC sınıflandırması:
  • HF5415.125
İçindekiler:
Why and whatis 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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Materyal türü Geçerli Kütüphane Yer numarası Durum Barkod
Book NEU Grand Library General Collection HF5415.125 .B47 2004 (Rafa gözat(Aşağıda açılır)) Kullanılabilir 4755845238

Includes index.

Why and whatis 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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