Data Mining and Knowledge Discovery with Evolutionary Algorithms

Data Mining and Knowledge Discovery with Evolutionary Algorithms

Author: Alex A. Freitas

Publisher: Springer Science & Business Media

Published: 2013-11-11

Total Pages: 272

ISBN-13: 3662049236

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This book integrates two areas of computer science, namely data mining and evolutionary algorithms. Both these areas have become increasingly popular in the last few years, and their integration is currently an active research area. In general, data mining consists of extracting knowledge from data. The motivation for applying evolutionary algorithms to data mining is that evolutionary algorithms are robust search methods which perform a global search in the space of candidate solutions. This book emphasizes the importance of discovering comprehensible, interesting knowledge, which is potentially useful for intelligent decision making. The text explains both basic concepts and advanced topics


Book Synopsis Data Mining and Knowledge Discovery with Evolutionary Algorithms by : Alex A. Freitas

Download or read book Data Mining and Knowledge Discovery with Evolutionary Algorithms written by Alex A. Freitas and published by Springer Science & Business Media. This book was released on 2013-11-11 with total page 272 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book integrates two areas of computer science, namely data mining and evolutionary algorithms. Both these areas have become increasingly popular in the last few years, and their integration is currently an active research area. In general, data mining consists of extracting knowledge from data. The motivation for applying evolutionary algorithms to data mining is that evolutionary algorithms are robust search methods which perform a global search in the space of candidate solutions. This book emphasizes the importance of discovering comprehensible, interesting knowledge, which is potentially useful for intelligent decision making. The text explains both basic concepts and advanced topics

Data Mining and Knowledge Discovery with Evolutionary Algorithms

Data Mining and Knowledge Discovery with Evolutionary Algorithms

Author: Alex A. Freitas

Publisher: Springer Science & Business Media

Published: 2002-08-21

Total Pages: 284

ISBN-13: 9783540433316

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This book integrates two areas of computer science, namely data mining and evolutionary algorithms. Both these areas have become increasingly popular in the last few years, and their integration is currently an active research area. In general, data mining consists of extracting knowledge from data. The motivation for applying evolutionary algorithms to data mining is that evolutionary algorithms are robust search methods which perform a global search in the space of candidate solutions. This book emphasizes the importance of discovering comprehensible, interesting knowledge, which is potentially useful for intelligent decision making. The text explains both basic concepts and advanced topics


Book Synopsis Data Mining and Knowledge Discovery with Evolutionary Algorithms by : Alex A. Freitas

Download or read book Data Mining and Knowledge Discovery with Evolutionary Algorithms written by Alex A. Freitas and published by Springer Science & Business Media. This book was released on 2002-08-21 with total page 284 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book integrates two areas of computer science, namely data mining and evolutionary algorithms. Both these areas have become increasingly popular in the last few years, and their integration is currently an active research area. In general, data mining consists of extracting knowledge from data. The motivation for applying evolutionary algorithms to data mining is that evolutionary algorithms are robust search methods which perform a global search in the space of candidate solutions. This book emphasizes the importance of discovering comprehensible, interesting knowledge, which is potentially useful for intelligent decision making. The text explains both basic concepts and advanced topics

Data Mining and Knowledge Discovery with Evolutionary Algorithms

Data Mining and Knowledge Discovery with Evolutionary Algorithms

Author: Alex A. Freitas

Publisher:

Published: 2014-01-15

Total Pages: 284

ISBN-13: 9783662049242

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Book Synopsis Data Mining and Knowledge Discovery with Evolutionary Algorithms by : Alex A. Freitas

Download or read book Data Mining and Knowledge Discovery with Evolutionary Algorithms written by Alex A. Freitas and published by . This book was released on 2014-01-15 with total page 284 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Multi-Objective Evolutionary Algorithms for Knowledge Discovery from Databases

Multi-Objective Evolutionary Algorithms for Knowledge Discovery from Databases

Author: Ashish Ghosh

Publisher: Springer Science & Business Media

Published: 2008-03-19

Total Pages: 169

ISBN-13: 3540774661

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The present volume provides a collection of seven articles containing new and high quality research results demonstrating the significance of Multi-objective Evolutionary Algorithms (MOEA) for data mining tasks in Knowledge Discovery from Databases (KDD). These articles are written by leading experts around the world. It is shown how the different MOEAs can be utilized, both in individual and integrated manner, in various ways to efficiently mine data from large databases.


Book Synopsis Multi-Objective Evolutionary Algorithms for Knowledge Discovery from Databases by : Ashish Ghosh

Download or read book Multi-Objective Evolutionary Algorithms for Knowledge Discovery from Databases written by Ashish Ghosh and published by Springer Science & Business Media. This book was released on 2008-03-19 with total page 169 pages. Available in PDF, EPUB and Kindle. Book excerpt: The present volume provides a collection of seven articles containing new and high quality research results demonstrating the significance of Multi-objective Evolutionary Algorithms (MOEA) for data mining tasks in Knowledge Discovery from Databases (KDD). These articles are written by leading experts around the world. It is shown how the different MOEAs can be utilized, both in individual and integrated manner, in various ways to efficiently mine data from large databases.

Data Mining And Knowledge Discovery With Evolutionary Algorithms

Data Mining And Knowledge Discovery With Evolutionary Algorithms

Author: Freitas Alex A.

Publisher:

Published: 2007-10-01

Total Pages: 265

ISBN-13: 9788181287915

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Book Synopsis Data Mining And Knowledge Discovery With Evolutionary Algorithms by : Freitas Alex A.

Download or read book Data Mining And Knowledge Discovery With Evolutionary Algorithms written by Freitas Alex A. and published by . This book was released on 2007-10-01 with total page 265 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Evolutionary Computation in Data Mining

Evolutionary Computation in Data Mining

Author: Ashish Ghosh

Publisher: Springer

Published: 2006-06-22

Total Pages: 279

ISBN-13: 3540323589

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Data mining (DM) consists of extracting interesting knowledge from re- world, large & complex data sets; and is the core step of a broader process, called the knowledge discovery from databases (KDD) process. In addition to the DM step, which actually extracts knowledge from data, the KDD process includes several preprocessing (or data preparation) and post-processing (or knowledge refinement) steps. The goal of data preprocessing methods is to transform the data to facilitate the application of a (or several) given DM algorithm(s), whereas the goal of knowledge refinement methods is to validate and refine discovered knowledge. Ideally, discovered knowledge should be not only accurate, but also comprehensible and interesting to the user. The total process is highly computation intensive. The idea of automatically discovering knowledge from databases is a very attractive and challenging task, both for academia and for industry. Hence, there has been a growing interest in data mining in several AI-related areas, including evolutionary algorithms (EAs). The main motivation for applying EAs to KDD tasks is that they are robust and adaptive search methods, which perform a global search in the space of candidate solutions (for instance, rules or another form of knowledge representation).


Book Synopsis Evolutionary Computation in Data Mining by : Ashish Ghosh

Download or read book Evolutionary Computation in Data Mining written by Ashish Ghosh and published by Springer. This book was released on 2006-06-22 with total page 279 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data mining (DM) consists of extracting interesting knowledge from re- world, large & complex data sets; and is the core step of a broader process, called the knowledge discovery from databases (KDD) process. In addition to the DM step, which actually extracts knowledge from data, the KDD process includes several preprocessing (or data preparation) and post-processing (or knowledge refinement) steps. The goal of data preprocessing methods is to transform the data to facilitate the application of a (or several) given DM algorithm(s), whereas the goal of knowledge refinement methods is to validate and refine discovered knowledge. Ideally, discovered knowledge should be not only accurate, but also comprehensible and interesting to the user. The total process is highly computation intensive. The idea of automatically discovering knowledge from databases is a very attractive and challenging task, both for academia and for industry. Hence, there has been a growing interest in data mining in several AI-related areas, including evolutionary algorithms (EAs). The main motivation for applying EAs to KDD tasks is that they are robust and adaptive search methods, which perform a global search in the space of candidate solutions (for instance, rules or another form of knowledge representation).

Data Mining Methods for Knowledge Discovery

Data Mining Methods for Knowledge Discovery

Author: Krzysztof J. Cios

Publisher: Springer Science & Business Media

Published: 2012-12-06

Total Pages: 508

ISBN-13: 1461555892

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Data Mining Methods for Knowledge Discovery provides an introduction to the data mining methods that are frequently used in the process of knowledge discovery. This book first elaborates on the fundamentals of each of the data mining methods: rough sets, Bayesian analysis, fuzzy sets, genetic algorithms, machine learning, neural networks, and preprocessing techniques. The book then goes on to thoroughly discuss these methods in the setting of the overall process of knowledge discovery. Numerous illustrative examples and experimental findings are also included. Each chapter comes with an extensive bibliography. Data Mining Methods for Knowledge Discovery is intended for senior undergraduate and graduate students, as well as a broad audience of professionals in computer and information sciences, medical informatics, and business information systems.


Book Synopsis Data Mining Methods for Knowledge Discovery by : Krzysztof J. Cios

Download or read book Data Mining Methods for Knowledge Discovery written by Krzysztof J. Cios and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 508 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data Mining Methods for Knowledge Discovery provides an introduction to the data mining methods that are frequently used in the process of knowledge discovery. This book first elaborates on the fundamentals of each of the data mining methods: rough sets, Bayesian analysis, fuzzy sets, genetic algorithms, machine learning, neural networks, and preprocessing techniques. The book then goes on to thoroughly discuss these methods in the setting of the overall process of knowledge discovery. Numerous illustrative examples and experimental findings are also included. Each chapter comes with an extensive bibliography. Data Mining Methods for Knowledge Discovery is intended for senior undergraduate and graduate students, as well as a broad audience of professionals in computer and information sciences, medical informatics, and business information systems.

Advanced Techniques in Knowledge Discovery and Data Mining

Advanced Techniques in Knowledge Discovery and Data Mining

Author: Nikhil Pal

Publisher: Springer Science & Business Media

Published: 2007-12-31

Total Pages: 264

ISBN-13: 1846281830

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Clear and concise explanations to understand the learning paradigms. Chapters written by leading world experts.


Book Synopsis Advanced Techniques in Knowledge Discovery and Data Mining by : Nikhil Pal

Download or read book Advanced Techniques in Knowledge Discovery and Data Mining written by Nikhil Pal and published by Springer Science & Business Media. This book was released on 2007-12-31 with total page 264 pages. Available in PDF, EPUB and Kindle. Book excerpt: Clear and concise explanations to understand the learning paradigms. Chapters written by leading world experts.

Soft Computing for Knowledge Discovery and Data Mining

Soft Computing for Knowledge Discovery and Data Mining

Author: Oded Maimon

Publisher: Springer Science & Business Media

Published: 2007-10-25

Total Pages: 431

ISBN-13: 038769935X

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Data Mining is the science and technology of exploring large and complex bodies of data in order to discover useful patterns. It is extremely important because it enables modeling and knowledge extraction from abundant data availability. This book introduces soft computing methods extending the envelope of problems that data mining can solve efficiently. It presents practical soft-computing approaches in data mining and includes various real-world case studies with detailed results.


Book Synopsis Soft Computing for Knowledge Discovery and Data Mining by : Oded Maimon

Download or read book Soft Computing for Knowledge Discovery and Data Mining written by Oded Maimon and published by Springer Science & Business Media. This book was released on 2007-10-25 with total page 431 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data Mining is the science and technology of exploring large and complex bodies of data in order to discover useful patterns. It is extremely important because it enables modeling and knowledge extraction from abundant data availability. This book introduces soft computing methods extending the envelope of problems that data mining can solve efficiently. It presents practical soft-computing approaches in data mining and includes various real-world case studies with detailed results.

Mathematical Methods for Knowledge Discovery and Data Mining

Mathematical Methods for Knowledge Discovery and Data Mining

Author: Felici, Giovanni

Publisher: IGI Global

Published: 2007-10-31

Total Pages: 394

ISBN-13: 1599045303

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"This book focuses on the mathematical models and methods that support most data mining applications and solution techniques, covering such topics as association rules; Bayesian methods; data visualization; kernel methods; neural networks; text, speech, and image recognition; an invaluable resource for scholars and practitioners in the fields of biomedicine, engineering, finance, manufacturing, marketing, performance measurement, and telecommunications"--Provided by publisher.


Book Synopsis Mathematical Methods for Knowledge Discovery and Data Mining by : Felici, Giovanni

Download or read book Mathematical Methods for Knowledge Discovery and Data Mining written by Felici, Giovanni and published by IGI Global. This book was released on 2007-10-31 with total page 394 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This book focuses on the mathematical models and methods that support most data mining applications and solution techniques, covering such topics as association rules; Bayesian methods; data visualization; kernel methods; neural networks; text, speech, and image recognition; an invaluable resource for scholars and practitioners in the fields of biomedicine, engineering, finance, manufacturing, marketing, performance measurement, and telecommunications"--Provided by publisher.