Data Mining: Concepts, Models, Methods and Algorithms - Brossura

Kantardzic, Mehmed

Brossura

ISBN 10: 0471228524 ISBN 13: 9780471228523

Casa editrice: IEEE, 2002

Riassunto

A comprehensive introduction to the exploding field of data mining

We are surrounded by data, numerical and otherwise, which must be analyzed and processed to convert it into information that informs, instructs, answers, or otherwise aids understanding and decision-making. Due to the ever-increasing complexity and size of today's data sets, a new term, data mining, was created to describe the indirect, automatic data analysis techniques that utilize more complex and sophisticated tools than those which analysts used in the past to do mere data analysis.

Data Mining: Concepts, Models, Methods, and Algorithms discusses data mining principles and then describes representative state-of-the-art methods and algorithms originating from different disciplines such as statistics, machine learning, neural networks, fuzzy logic, and evolutionary computation. Detailed algorithms are provided with necessary explanations and illustrative examples.

This text offers guidance: how and when to use a particular software tool (with their companion data sets) from among the hundreds offered when faced with a data set to mine. This allows analysts to create and perform their own data mining experiments using their knowledge of the methodologies and techniques provided.

This book emphasizes the selection of appropriate methodologies and data analysis software, as well as parameter tuning. These critically important, qualitative decisions can only be made with the deeper understanding of parameter meaning and its role in the technique that is offered here. Data mining is an exploding field and this book offers much-needed guidance to selecting among the numerous analysis programs that are available.

Su questo libro

Informazioni sull?autore

MEHMED KANTARDZIC, PhD, is an associate professor in the Department of Computer Engineering and Computer Science (CECS) at the University of Louisville, and is Director of the Data Mining Lab. He was a visiting faculty member in the CECS from 1995 until August 2001. Dr. Kantardzic earned his PhD in 1980 at the University of Sarajevo, Bosnia, where he was an associate professor and Head of the Laboratory for Electronics and Computer Science until 1994.

Dalla quarta di copertina

A comprehensive introduction to the exploding field of data mining

We are surrounded by data, numerical and otherwise, which must be analyzed and processed to convert it into information that informs, instructs, answers, or otherwise aids understanding and decision-making. Due to the ever-increasing complexity and size of today's data sets, a new term, data mining, was created to describe the indirect, automatic data analysis techniques that utilize more complex and sophisticated tools than those which analysts used in the past to do mere data analysis.

Data Mining: Concepts, Models, Methods, and Algorithms discusses data mining principles and then describes representative state-of-the-art methods and algorithms originating from different disciplines such as statistics, machine learning, neural networks, fuzzy logic, and evolutionary computation. Detailed algorithms are provided with necessary explanations and illustrative examples.

This text offers guidance: how and when to use a particular software tool (with their companion data sets) from among the hundreds offered when faced with a data set to mine. This allows analysts to create and perform their own data mining experiments using their knowledge of the methodologies and techniques provided.

This book emphasizes the selection of appropriate methodologies and data analysis software, as well as parameter tuning. These critically important, qualitative decisions can only be made with the deeper understanding of parameter meaning and its role in the technique that is offered here. Data mining is an exploding field and this book offers much-needed guidance to selecting among the numerous analysis programs that are available.

Dettagli dell?edizione

• Editore: IEEE
• Data di pubblicazione: 2002
• Lingua: Inglese
• ISBN 10: 0471228524
• ISBN 13: 9780471228523
• Rilegatura: Copertina flessibile
• Numero edizione: 1
• Numero di pagine: 344
• Contatto del produttore: non disponibile
• Persona responsabile: non disponibile