Data Mining Methods for Knowledge Discovery

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Release : 2012-12-06
Genre : Computers
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Book Rating : 892/5 ( reviews)

Data Mining Methods for Knowledge Discovery - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Data Mining Methods for Knowledge Discovery write by Krzysztof J. Cios. This book was released on 2012-12-06. Data Mining Methods for Knowledge Discovery available in PDF, EPUB and Kindle. 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.

Knowledge Discovery and Data Mining

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Release : 2000-12-31
Genre : Computers
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Book Rating : 478/5 ( reviews)

Knowledge Discovery and Data Mining - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Knowledge Discovery and Data Mining write by O. Maimon. This book was released on 2000-12-31. Knowledge Discovery and Data Mining available in PDF, EPUB and Kindle. This book presents a specific and unified approach to Knowledge Discovery and Data Mining, termed IFN for Information Fuzzy Network methodology. Data Mining (DM) is the science of modelling and generalizing common patterns from large sets of multi-type data. DM is a part of KDD, which is the overall process for Knowledge Discovery in Databases. The accessibility and abundance of information today makes this a topic of particular importance and need. The book has three main parts complemented by appendices as well as software and project data that are accessible from the book's web site (http://www.eng.tau.ac.iV-maimonlifn-kdg£). Part I (Chapters 1-4) starts with the topic of KDD and DM in general and makes reference to other works in the field, especially those related to the information theoretic approach. The remainder of the book presents our work, starting with the IFN theory and algorithms. Part II (Chapters 5-6) discusses the methodology of application and includes case studies. Then in Part III (Chapters 7-9) a comparative study is presented, concluding with some advanced methods and open problems. The IFN, being a generic methodology, applies to a variety of fields, such as manufacturing, finance, health care, medicine, insurance, and human resources. The appendices expand on the relevant theoretical background and present descriptions of sample projects (including detailed results).

Data Mining

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Release : 2007-10-05
Genre : Computers
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Book Rating : 950/5 ( reviews)

Data Mining - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Data Mining write by Krzysztof J. Cios. This book was released on 2007-10-05. Data Mining available in PDF, EPUB and Kindle. This comprehensive textbook on data mining details the unique steps of the knowledge discovery process that prescribes the sequence in which data mining projects should be performed, from problem and data understanding through data preprocessing to deployment of the results. This knowledge discovery approach is what distinguishes Data Mining from other texts in this area. The book provides a suite of exercises and includes links to instructional presentations. Furthermore, it contains appendices of relevant mathematical material.

Data Mining and Knowledge Discovery Handbook

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Release : 2006-05-28
Genre : Computers
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Book Rating : 65X/5 ( reviews)

Data Mining and Knowledge Discovery Handbook - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Data Mining and Knowledge Discovery Handbook write by Oded Maimon. This book was released on 2006-05-28. Data Mining and Knowledge Discovery Handbook available in PDF, EPUB and Kindle. Data Mining and Knowledge Discovery Handbook organizes all major concepts, theories, methodologies, trends, challenges and applications of data mining (DM) and knowledge discovery in databases (KDD) into a coherent and unified repository. This book first surveys, then provides comprehensive yet concise algorithmic descriptions of methods, including classic methods plus the extensions and novel methods developed recently. This volume concludes with in-depth descriptions of data mining applications in various interdisciplinary industries including finance, marketing, medicine, biology, engineering, telecommunications, software, and security. Data Mining and Knowledge Discovery Handbook is designed for research scientists and graduate-level students in computer science and engineering. This book is also suitable for professionals in fields such as computing applications, information systems management, and strategic research management.

Urban Informatics

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Release : 2021-04-06
Genre : Social Science
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Book Rating : 836/5 ( reviews)

Urban Informatics - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Urban Informatics write by Wenzhong Shi. This book was released on 2021-04-06. Urban Informatics available in PDF, EPUB and Kindle. This open access book is the first to systematically introduce the principles of urban informatics and its application to every aspect of the city that involves its functioning, control, management, and future planning. It introduces new models and tools being developed to understand and implement these technologies that enable cities to function more efficiently – to become ‘smart’ and ‘sustainable’. The smart city has quickly emerged as computers have become ever smaller to the point where they can be embedded into the very fabric of the city, as well as being central to new ways in which the population can communicate and act. When cities are wired in this way, they have the potential to become sentient and responsive, generating massive streams of ‘big’ data in real time as well as providing immense opportunities for extracting new forms of urban data through crowdsourcing. This book offers a comprehensive review of the methods that form the core of urban informatics from various kinds of urban remote sensing to new approaches to machine learning and statistical modelling. It provides a detailed technical introduction to the wide array of tools information scientists need to develop the key urban analytics that are fundamental to learning about the smart city, and it outlines ways in which these tools can be used to inform design and policy so that cities can become more efficient with a greater concern for environment and equity.