Advanced Data Mining Techniques (häftad)
Format
Häftad (Paperback / softback)
Språk
Engelska
Antal sidor
180
Utgivningsdatum
2008-01-01
Upplaga
2008 ed.
Förlag
Springer-Verlag Berlin and Heidelberg GmbH & Co. K
Medarbetare
Delen, Dursun
Illustratör/Fotograf
8 schw-w Zeichn 21 schw-w Abb, 13 schw-w Fotos 57 schw-w Tabellen
Illustrationer
21 Illustrations, black and white; XII, 180 p. 21 illus.
Dimensioner
232 x 158 x 11 mm
Vikt
300 g
Antal komponenter
1
Komponenter
1 Paperback / softback
ISBN
9783540769163

Advanced Data Mining Techniques

Häftad,  Engelska, 2008-01-01
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The intent of this book is to describe some recent data mining tools that have proven effective in dealing with data sets which often involve unc- tain description or other complexities that cause difficulty for the conv- tional approaches of logistic regression, neural network models, and de- sion trees. Among these traditional algorithms, neural network models often have a relative advantage when data is complex. We will discuss methods with simple examples, review applications, and evaluate relative advantages of several contemporary methods. Book Concept Our intent is to cover the fundamental concepts of data mining, to dem- strate the potential of gathering large sets of data, and analyzing these data sets to gain useful business understanding. We have organized the material into three parts. Part I introduces concepts. Part II contains chapters on a number of different techniques often used in data mining. Part III focuses on business applications of data mining. Not all of these chapters need to be covered, and their sequence could be varied at instructor design. The book will include short vignettes of how specific concepts have been applied in real practice. A series of representative data sets will be generated to demonstrate specific methods and concepts. References to data mining software and sites such as www.kdnuggets.com will be provided. Part I: Introduction Chapter 1 gives an overview of data mining, and provides a description of the data mining process. An overview of useful business applications is provided.
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From the reviews: "Text analysis and data mining have become increasingly important capabilities in todays information-flooded world, and choosing the right technique makes all the difference. This book contains some advanced data mining techniques, but also includes an overview of important data mining fundamentals, specifically the CRISP-DM and SEMMA industry standards. Summing Up: Recommended. Upper-division undergraduates and up." (H. J. Bender, CHOICE, Vol. 45 (11), August, 2008)

Innehållsförteckning

Data Mining Process.- Data Mining Methods As Tools.- Memory-Based Reasoning Methods.- Association Rules in Knowledge Discovery.- Fuzzy Sets in Data Mining.- Rough Sets.- Support Vector Machines.- Genetic Algorithm Support to Data Mining.- Performance Evaluation for Predictive Modeling.- Applications.- Applications of Methods.