Soft Computing for Knowledge Discovery, James G. Shanahan
Автор: Oded Maimon; Lior Rokach Название: Soft Computing for Knowledge Discovery and Data Mining ISBN: 144194351X ISBN-13(EAN): 9781441943514 Издательство: Springer Рейтинг: Цена: 83850.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание:
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.
Soft Computing for Knowledge Discovery and Data Mining introduces soft computing methods extending the envelope of problems that data mining can solve efficiently. It presents practical soft-computing approaches in data mining. This edited volume by highly regarded authors, includes several contributors of the 2005, Data Mining and Knowledge Discovery Handbook. This book was written to provide investigators in the fields of information systems, engineering, computer science, statistics and management with a profound source for the role of soft computing in data mining. Not only does this book feature illustrations of various applications including manufacturing, medical, banking, insurance and others, but also includes various real-world case studies with detailed results.
Soft Computing for Knowledge Discovery and Data Mining is designed for practitioners and researchers in industry. Practitioners and researchers may be particularly interested in the description of real world data mining projects performed with soft computing. This book is also suitable as a secondary textbook or reference for advanced-level students in information systems, engineering, computer science and statistics management.
Автор: James G. Shanahan Название: Soft Computing for Knowledge Discovery ISBN: 1461369479 ISBN-13(EAN): 9781461369479 Издательство: Springer Рейтинг: Цена: 139750.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Knowledge discovery is an area of computer science that attempts to uncover interesting and useful patterns in data that permit a computer to perform a task autonomously or assist a human in performing a task more efficiently. Soft Computing for Knowledge Discovery provides a self-contained and systematic exposition of the key theory and algorithms that form the core of knowledge discovery from a soft computing perspective. It focuses on knowledge representation, machine learning, and the key methodologies that make up the fabric of soft computing - fuzzy set theory, fuzzy logic, evolutionary computing, and various theories of probability (e.g. na ve Bayes and Bayesian networks, Dempster-Shafer theory, mass assignment theory, and others). In addition to describing many state-of-the-art soft computing approaches to knowledge discovery, the author introduces Cartesian granulefeatures and their corresponding learning algorithms as an intuitive approach to knowledge discovery. This new approach embraces the synergistic spirit of soft computing and exploits uncertainty in order to achieve tractability, transparency and generalization. Parallels are drawn between this approach and other well known approaches (such as naive Bayes and decision trees) leading to equivalences under certain conditions. The approaches presented are further illustrated in a battery of both artificial and real-world problems. Knowledge discovery in real-world problems, such as object recognition in outdoor scenes, medical diagnosis and control, is described in detail. These case studies provide further examples of how to apply the presented concepts and algorithms to practical problems. The author provides web page access to an online bibliography, datasets, source codes for several algorithms described in the book, and other information. Soft Computing for Knowledge Discovery is for advanced undergraduates, professionals and researchers in computer science, engineering and business information systems who work or have an interest in the dynamic fields of knowledge discovery and soft computing.
Автор: Andrew Stranieri; John Zeleznikow Название: Knowledge Discovery from Legal Databases ISBN: 904816771X ISBN-13(EAN): 9789048167715 Издательство: Springer Рейтинг: Цена: 181670.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Knowledge Discovery from Legal Databases is the first text to describe data mining techniques as they apply to law.
Автор: Tsau Young Lin; Setsuo Ohsuga; Churn-Jung Liau; Xi Название: Foundations of Data Mining and Knowledge Discovery ISBN: 364243228X ISBN-13(EAN): 9783642432286 Издательство: Springer Рейтинг: Цена: 181670.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: "Foundations of Data Mining and Knowledge Discovery" contains the latest results and new directions in data mining research.
Автор: Chu Wesley W. Название: Data Mining and Knowledge Discovery for Big Data ISBN: 3642408362 ISBN-13(EAN): 9783642408366 Издательство: Springer Рейтинг: Цена: 139310.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book address topics ranging from mining data from opinion, spatiotemporal databases, discriminative subgraph patterns, path knowledge discovery, social media, and privacy issues to the subject of computation reduction via binary matrix factorization.
Автор: Tsau Young Lin; Setsuo Ohsuga; Churn-Jung Liau; Xi Название: Foundations of Data Mining and Knowledge Discovery ISBN: 3540262571 ISBN-13(EAN): 9783540262572 Издательство: Springer Рейтинг: Цена: 181670.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: "Foundations of Data Mining and Knowledge Discovery" contains the latest results and new directions in data mining research.
Автор: Saman K. Halgamuge; Lipo Wang Название: Classification and Clustering for Knowledge Discovery ISBN: 3642065422 ISBN-13(EAN): 9783642065422 Издательство: Springer Рейтинг: Цена: 194730.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book covers recent advances in unsupervised and supervised data analysis methods in Computational Intelligence for knowledge discovery. If labeled data or data with known associations are available, we may be able to use supervised data analysis methods, such as classifying neural networks, fuzzy rule-based classifiers, and decision trees.
Автор: Evangelos Triantaphyllou; Giovanni Felici Название: Data Mining and Knowledge Discovery Approaches Based on Rule Induction Techniques ISBN: 1441941738 ISBN-13(EAN): 9781441941732 Издательство: Springer Рейтинг: Цена: 222670.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book outlines the core theory and practice of data mining and knowledge discovery (DM & KD) examining theoretical foundations for various methods, and presenting an array of examples, many drawn from real-life applications.
Автор: Il-Yeol Song; Johann Eder; Tho Manh Nguyen Название: Data Warehousing and Knowledge Discovery ISBN: 3540858350 ISBN-13(EAN): 9783540858355 Издательство: Springer Рейтинг: Цена: 81050.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Includes the refereed proceedings of the 10th International Conference on Data Warehousing and Knowledge Discovery, DaWak 2008, held in Turin, Italy, in September 2008. This book contains 40 papers that were selected from 143 submissions.
Автор: Fabrice Guillet; Gilbert Ritschard; Djamel A. Zigh Название: Advances in Knowledge Discovery and Management ISBN: 3642005799 ISBN-13(EAN): 9783642005794 Издательство: Springer Рейтинг: Цена: 204040.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Reflecting recent advances in the field of data mining and knowledge discovery achieved by Francophone scientists in France and elsewhere, this collection of extended and reworked papers were originally presented at the EGC 2009 conference in Strasbourg.
Автор: Fabrice Guillet; Gilbert Ritschard; Djamel A. Zigh Название: Advances in Knowledge Discovery and Management ISBN: 3642263712 ISBN-13(EAN): 9783642263712 Издательство: Springer Рейтинг: Цена: 204040.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Reflecting recent advances in the field of data mining and knowledge discovery achieved by Francophone scientists in France and elsewhere, this collection of extended and reworked papers were originally presented at the EGC 2009 conference in Strasbourg.
Автор: Fabrice Guillet; Gilbert Ritschard; Djamel Abdelka Название: Advances in Knowledge Discovery and Management ISBN: 3642427790 ISBN-13(EAN): 9783642427794 Издательство: Springer Рейтинг: Цена: 121890.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: KDM, which includes techniques such as data mining and business intelligence, is a fruitful research topic in the French-speaking scientific community, where it is known as EGC. This volume is a selection of the best papers from the EGC 2010 conference.
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