Data Mining Techniques

Michael J.A. Berry, Gordon Linoff

643 pages, parution le 23/04/2004 (2^eme édition)

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Résumé

Packed with more than forty percent new and updated material, this edition shows business managers, marketing analysts, and data mining specialists how to harness fundamental data mining methods and techniques to solve common types of business problems
Each chapter covers a new data mining technique, and then shows readers how to apply the technique for improved marketing, sales, and customer support
The authors build on their reputation for concise, clear, and practical explanations of complex concepts, making this book the perfect introduction to data mining
More advanced chapters cover such topics as how to prepare data for analysis and how to create the necessary infrastructure for data mining
Covers core data mining techniques, including decision trees, neural networks, collaborative filtering, association rules, link analysis, clustering, and survival analysis

L'auteur - Michael J.A. Berry

Michael J. A. Berry

has twenty years experience applying advanced data mining techniques, data warehousing designs, developing Internet and intranet solutions, providing decision support, providing full text information retrieval capability, and designing and implementing software applications.

L'auteur - Gordon Linoff

Gordon S. Linoff

is a founder and principal consultant with Data Miners. He has fourteen years of professional experience as a software engineer and consultant. He is a frequent speaker on using technology to enable organizations to realize the potential of one-to-one marketing using data warehousing and data mining. Mr. Linoff has extensive experience in the telecommunications, finance, medical, and retail industries in both data mining and data warehousing.

Sommaire

Introduction
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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Caractéristiques techniques

	PAPIER
Éditeur(s)	Wiley
Auteur(s)	Michael J.A. Berry, Gordon Linoff
Parution	23/04/2004
Édition	2^eme édition
Nb. de pages	643
Format	18,5 x 23,5
Couverture	Broché
Poids	995g
Intérieur	Noir et Blanc
EAN13	9780471470649