Read Books Online and Download eBooks, EPub, PDF, Mobi, Kindle, Text Full Free.
Computational Intelligence In Data Mining Volume 1
Download Computational Intelligence In Data Mining Volume 1 full books in PDF, epub, and Kindle. Read online Computational Intelligence In Data Mining Volume 1 ebook anywhere anytime directly on your device. Fast Download speed and no annoying ads. We cannot guarantee that every ebooks is available!
Book Synopsis Data Mining with Computational Intelligence by : Lipo Wang
Download or read book Data Mining with Computational Intelligence written by Lipo Wang and published by Springer Science & Business Media. This book was released on 2005-12-08 with total page 280 pages. Available in PDF, EPUB and Kindle. Book excerpt: Finding information hidden in data is as theoretically difficult as it is practically important. With the objective of discovering unknown patterns from data, the methodologies of data mining were derived from statistics, machine learning, and artificial intelligence, and are being used successfully in application areas such as bioinformatics, banking, retail, and many others. Wang and Fu present in detail the state of the art on how to utilize fuzzy neural networks, multilayer perceptron neural networks, radial basis function neural networks, genetic algorithms, and support vector machines in such applications. They focus on three main data mining tasks: data dimensionality reduction, classification, and rule extraction. The book is targeted at researchers in both academia and industry, while graduate students and developers of data mining systems will also profit from the detailed algorithmic descriptions.
Book Synopsis Computational Intelligence in Data Mining by : Janmenjoy Nayak
Download or read book Computational Intelligence in Data Mining written by Janmenjoy Nayak and published by Springer Nature. This book was released on 2022-05-06 with total page 757 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book addresses different methods and techniques of integration for enhancing the overall goal of data mining. The book is a collection of high-quality peer-reviewed research papers presented in the Sixth International Conference on Computational Intelligence in Data Mining (ICCIDM 2021) held at Aditya Institute of Technology and Management, Tekkali, Andhra Pradesh, India, during December 11–12, 2021. The book addresses the difficulties and challenges for the seamless integration of two core disciplines of computer science, i.e., computational intelligence and data mining. The book helps to disseminate the knowledge about some innovative, active research directions in the field of data mining, machine and computational intelligence, along with some current issues and applications of related topics.
Book Synopsis Computational Intelligence in Data Mining - Volume 1 by : Lakhmi C. Jain
Download or read book Computational Intelligence in Data Mining - Volume 1 written by Lakhmi C. Jain and published by Springer. This book was released on 2014-12-10 with total page 713 pages. Available in PDF, EPUB and Kindle. Book excerpt: The contributed volume aims to explicate and address the difficulties and challenges for the seamless integration of two core disciplines of computer science, i.e., computational intelligence and data mining. Data Mining aims at the automatic discovery of underlying non-trivial knowledge from datasets by applying intelligent analysis techniques. The interest in this research area has experienced a considerable growth in the last years due to two key factors: (a) knowledge hidden in organizations’ databases can be exploited to improve strategic and managerial decision-making; (b) the large volume of data managed by organizations makes it impossible to carry out a manual analysis. The book addresses different methods and techniques of integration for enhancing the overall goal of data mining. The book helps to disseminate the knowledge about some innovative, active research directions in the field of data mining, machine and computational intelligence, along with some current issues and applications of related topics.
Book Synopsis Computational Intelligence in Data Mining—Volume 1 by : Himansu Sekhar Behera
Download or read book Computational Intelligence in Data Mining—Volume 1 written by Himansu Sekhar Behera and published by Springer. This book was released on 2015-12-08 with total page 494 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book is a collection of high-quality peer-reviewed research papers presented in the Second International Conference on Computational Intelligence in Data Mining (ICCIDM 2015) held at Bhubaneswar, Odisha, India during 5 – 6 December 2015. The two-volume Proceedings address the difficulties and challenges for the seamless integration of two core disciplines of computer science, i.e., computational intelligence and data mining. The book addresses different methods and techniques of integration for enhancing the overall goal of data mining. The book helps to disseminate the knowledge about some innovative, active research directions in the field of data mining, machine and computational intelligence, along with some current issues and applications of related topics.
Book Synopsis Foundations of Computational Intelligence by : Ajith Abraham
Download or read book Foundations of Computational Intelligence written by Ajith Abraham and published by Springer. This book was released on 2009-05-01 with total page 400 pages. Available in PDF, EPUB and Kindle. Book excerpt: Foundations of Computational Intelligence Volume 6: Data Mining: Theoretical Foundations and Applications Finding information hidden in data is as theoretically difficult as it is practically important. With the objective of discovering unknown patterns from data, the methodologies of data mining were derived from statistics, machine learning, and artificial intelligence, and are being used successfully in application areas such as bioinformatics, business, health care, banking, retail, and many others. Advanced representation schemes and computational intelligence techniques such as rough sets, neural networks; decision trees; fuzzy logic; evolutionary algorithms; arti- cial immune systems; swarm intelligence; reinforcement learning, association rule mining, Web intelligence paradigms etc. have proved valuable when they are - plied to Data Mining problems. Computational tools or solutions based on intel- gent systems are being used with great success in Data Mining applications. It is also observed that strong scientific advances have been made when issues from different research areas are integrated. This Volume comprises of 15 chapters including an overview chapter providing an up-to-date and state-of-the research on the applications of Computational Int- ligence techniques for Data Mining. The book is divided into 3 parts: Part-I: Data Click Streams and Temporal Data Mining Part-II: Text and Rule Mining Part-III: Applications Part I on Data Click Streams and Temporal Data Mining contains four chapters that describe several approaches in Data Click Streams and Temporal Data Mining.
Book Synopsis Computational Intelligence in Data Mining by : Giacomo Della Riccia
Download or read book Computational Intelligence in Data Mining written by Giacomo Della Riccia and published by . This book was released on 2014-09-01 with total page 176 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Computational Intelligence in Data Mining by : Himansu Sekhar Behera
Download or read book Computational Intelligence in Data Mining written by Himansu Sekhar Behera and published by Springer. This book was released on 2017-05-19 with total page 847 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book presents high quality papers presented at the International Conference on Computational Intelligence in Data Mining (ICCIDM 2016) organized by School of Computer Engineering, Kalinga Institute of Industrial Technology (KIIT), Bhubaneswar, Odisha, India during December 10 – 11, 2016. The book disseminates the knowledge about innovative, active research directions in the field of data mining, machine and computational intelligence, along with current issues and applications of related topics. The volume aims to explicate and address the difficulties and challenges that of seamless integration of the two core disciplines of computer science.
Book Synopsis Computational Intelligence in Data Mining by : Himansu Sekhar Behera
Download or read book Computational Intelligence in Data Mining written by Himansu Sekhar Behera and published by Springer. This book was released on 2019-08-17 with total page 801 pages. Available in PDF, EPUB and Kindle. Book excerpt: This proceeding discuss the latest solutions, scientific findings and methods for solving intriguing problems in the fields of data mining, computational intelligence, big data analytics, and soft computing. This gathers outstanding papers from the fifth International Conference on “Computational Intelligence in Data Mining” (ICCIDM), and offer a “sneak preview” of the strengths and weaknesses of trending applications, together with exciting advances in computational intelligence, data mining, and related fields.
Book Synopsis Data Mining With Computational Intelligence by : Wang
Download or read book Data Mining With Computational Intelligence written by Wang and published by . This book was released on 2009-10-01 with total page 288 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Computational Intelligence in Data Mining by : Himansu Sekhar Behera
Download or read book Computational Intelligence in Data Mining written by Himansu Sekhar Behera and published by Springer. This book was released on 2018-07-03 with total page 896 pages. Available in PDF, EPUB and Kindle. Book excerpt: The International Conference on “Computational Intelligence in Data Mining” (ICCIDM), after three successful versions, has reached to its fourth version with a lot of aspiration. The best selected conference papers are reviewed and compiled to form this volume. The proceedings discusses the latest solutions, scientific results and methods in solving intriguing problems in the fields of data mining, computational intelligence, big data analytics, and soft computing. The volume presents a sneak preview into the strengths and weakness of trending applications and research findings in the field of computational intelligence and data mining along with related field.
Book Synopsis Computational Intelligence in Data Mining—Volume 2 by : Himansu Sekhar Behera
Download or read book Computational Intelligence in Data Mining—Volume 2 written by Himansu Sekhar Behera and published by Springer. This book was released on 2015-12-09 with total page 520 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book is a collection of high-quality peer-reviewed research papers presented in the Second International Conference on Computational Intelligence in Data Mining (ICCIDM 2015) held at Bhubaneswar, Odisha, India during 5 – 6 December 2015. The two-volume Proceedings address the difficulties and challenges for the seamless integration of two core disciplines of computer science, i.e., computational intelligence and data mining. The book addresses different methods and techniques of integration for enhancing the overall goal of data mining. The book helps to disseminate the knowledge about some innovative, active research directions in the field of data mining, machine and computational intelligence, along with some current issues and applications of related topics.
Book Synopsis Data Mining: Foundations and Practice by : Tsau Young Lin
Download or read book Data Mining: Foundations and Practice written by Tsau Young Lin and published by Springer. This book was released on 2008-08-17 with total page 562 pages. Available in PDF, EPUB and Kindle. Book excerpt: The IEEE ICDM 2004 workshop on the Foundation of Data Mining and the IEEE ICDM 2005 workshop on the Foundation of Semantic Oriented Data and Web Mining focused on topics ranging from the foundations of data mining to new data mining paradigms. The workshops brought together both data mining researchers and practitioners to discuss these two topics while seeking solutions to long standing data mining problems and stimul- ing new data mining research directions. We feel that the papers presented at these workshops may encourage the study of data mining as a scienti?c ?eld and spark new communications and collaborations between researchers and practitioners. Toexpressthevisionsforgedintheworkshopstoawiderangeofdatam- ing researchers and practitioners and foster active participation in the study of foundations of data mining, we edited this volume by involving extended and updated versions of selected papers presented at those workshops as well as some other relevant contributions. The content of this book includes st- ies of foundations of data mining from theoretical, practical, algorithmical, and managerial perspectives. The following is a brief summary of the papers contained in this book.
Book Synopsis Computational Intelligence in Data Mining - Volume 2 by : Lakhmi C. Jain
Download or read book Computational Intelligence in Data Mining - Volume 2 written by Lakhmi C. Jain and published by Springer. This book was released on 2014-12-10 with total page 707 pages. Available in PDF, EPUB and Kindle. Book excerpt: The contributed volume aims to explicate and address the difficulties and challenges that of seamless integration of the two core disciplines of computer science, i.e., computational intelligence and data mining. Data Mining aims at the automatic discovery of underlying non-trivial knowledge from datasets by applying intelligent analysis techniques. The interest in this research area has experienced a considerable growth in the last years due to two key factors: (a) knowledge hidden in organizations’ databases can be exploited to improve strategic and managerial decision-making; (b) the large volume of data managed by organizations makes it impossible to carry out a manual analysis. The book addresses different methods and techniques of integration for enhancing the overall goal of data mining. The book helps to disseminate the knowledge about some innovative, active research directions in the field of data mining, machine and computational intelligence, along with some current issues and applications of related topics.
Book Synopsis Introduction to Data Mining and its Applications by : S. Sumathi
Download or read book Introduction to Data Mining and its Applications written by S. Sumathi and published by Springer. This book was released on 2006-10-12 with total page 828 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book explores the concepts of data mining and data warehousing, a promising and flourishing frontier in database systems, and presents a broad, yet in-depth overview of the field of data mining. Data mining is a multidisciplinary field, drawing work from areas including database technology, artificial intelligence, machine learning, neural networks, statistics, pattern recognition, knowledge based systems, knowledge acquisition, information retrieval, high performance computing and data visualization.
Book Synopsis Computational Intelligence in Data Mining - Volume 3 by : Lakhmi C. Jain
Download or read book Computational Intelligence in Data Mining - Volume 3 written by Lakhmi C. Jain and published by Springer. This book was released on 2014-12-11 with total page 717 pages. Available in PDF, EPUB and Kindle. Book excerpt: The contributed volume aims to explicate and address the difficulties and challenges for the seamless integration of two core disciplines of computer science, i.e., computational intelligence and data mining. Data Mining aims at the automatic discovery of underlying non-trivial knowledge from datasets by applying intelligent analysis techniques. The interest in this research area has experienced a considerable growth in the last years due to two key factors: (a) knowledge hidden in organizations’ databases can be exploited to improve strategic and managerial decision-making; (b) the large volume of data managed by organizations makes it impossible to carry out a manual analysis. The book addresses different methods and techniques of integration for enhancing the overall goal of data mining. The book helps to disseminate the knowledge about some innovative, active research directions in the field of data mining, machine and computational intelligence, along with some current issues and applications of related topics.
Book Synopsis Foundations of Data Mining and Knowledge Discovery by : Tsau Young Lin
Download or read book Foundations of Data Mining and Knowledge Discovery written by Tsau Young Lin and published by Springer Science & Business Media. This book was released on 2005-09-02 with total page 400 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Foundations of Data Mining and Knowledge Discovery" contains the latest results and new directions in data mining research. Data mining, which integrates various technologies, including computational intelligence, database and knowledge management, machine learning, soft computing, and statistics, is one of the fastest growing fields in computer science. Although many data mining techniques have been developed, further development of the field requires a close examination of its foundations. This volume presents the results of investigations into the foundations of the discipline, and represents the state of the art for much of the current research. This book will prove extremely valuable and fruitful for data mining researchers, no matter whether they would like to uncover the fundamental principles behind data mining, or apply the theories to practical applications.
Book Synopsis Machine Learning and Data Mining by : Igor Kononenko
Download or read book Machine Learning and Data Mining written by Igor Kononenko and published by Elsevier. This book was released on 2007-04-30 with total page 480 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data mining is often referred to by real-time users and software solutions providers as knowledge discovery in databases (KDD). Good data mining practice for business intelligence (the art of turning raw software into meaningful information) is demonstrated by the many new techniques and developments in the conversion of fresh scientific discovery into widely accessible software solutions. This book has been written as an introduction to the main issues associated with the basics of machine learning and the algorithms used in data mining. Suitable for advanced undergraduates and their tutors at postgraduate level in a wide area of computer science and technology topics as well as researchers looking to adapt various algorithms for particular data mining tasks. A valuable addition to the libraries and bookshelves of the many companies who are using the principles of data mining (or KDD) to effectively deliver solid business and industry solutions. Provides an introduction to the main issues associated with the basics of machine learning and the algorithms used in data mining A valuable addition to the libraries and bookshelves of companies using the principles of data mining (or KDD) to effectively deliver solid business and industry solutions
