Computational Methods of Feature Selection

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Publisher : CRC Press
ISBN 13 : 1584888792
Total Pages : 437 pages
Book Rating : 4.96/5 ( download)

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Book Synopsis Computational Methods of Feature Selection by : Huan Liu

Download or read book Computational Methods of Feature Selection written by Huan Liu and published by CRC Press. This book was released on 2007-10-29 with total page 437 pages. Available in PDF, EPUB and Kindle. Book excerpt: Due to increasing demands for dimensionality reduction, research on feature selection has deeply and widely expanded into many fields, including computational statistics, pattern recognition, machine learning, data mining, and knowledge discovery. Highlighting current research issues, Computational Methods of Feature Selection introduces the

Computational Intelligence and Feature Selection

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Publisher : John Wiley & Sons
ISBN 13 : 0470377917
Total Pages : 357 pages
Book Rating : 4.18/5 ( download)

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Book Synopsis Computational Intelligence and Feature Selection by : Richard Jensen

Download or read book Computational Intelligence and Feature Selection written by Richard Jensen and published by John Wiley & Sons. This book was released on 2008-10-03 with total page 357 pages. Available in PDF, EPUB and Kindle. Book excerpt: The rough and fuzzy set approaches presented here open up many new frontiers for continued research and development Computational Intelligence and Feature Selection provides readers with the background and fundamental ideas behind Feature Selection (FS), with an emphasis on techniques based on rough and fuzzy sets. For readers who are less familiar with the subject, the book begins with an introduction to fuzzy set theory and fuzzy-rough set theory. Building on this foundation, the book provides: A critical review of FS methods, with particular emphasis on their current limitations Program files implementing major algorithms, together with the necessary instructions and datasets, available on a related Web site Coverage of the background and fundamental ideas behind FS A systematic presentation of the leading methods reviewed in a consistent algorithmic framework Real-world applications with worked examples that illustrate the power and efficacy of the FS approaches covered An investigation of the associated areas of FS, including rule induction and clustering methods using hybridizations of fuzzy and rough set theories Computational Intelligence and Feature Selection is an ideal resource for advanced undergraduates, postgraduates, researchers, and professional engineers. However, its straightforward presentation of the underlying concepts makes the book meaningful to specialists and nonspecialists alike.

Feature Engineering and Selection

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Publisher : CRC Press
ISBN 13 : 1351609467
Total Pages : 266 pages
Book Rating : 4.63/5 ( download)

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Book Synopsis Feature Engineering and Selection by : Max Kuhn

Download or read book Feature Engineering and Selection written by Max Kuhn and published by CRC Press. This book was released on 2019-07-25 with total page 266 pages. Available in PDF, EPUB and Kindle. Book excerpt: The process of developing predictive models includes many stages. Most resources focus on the modeling algorithms but neglect other critical aspects of the modeling process. This book describes techniques for finding the best representations of predictors for modeling and for nding the best subset of predictors for improving model performance. A variety of example data sets are used to illustrate the techniques along with R programs for reproducing the results.

Encyclopedia of Machine Learning

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Publisher : Springer Science & Business Media
ISBN 13 : 0387307680
Total Pages : 1061 pages
Book Rating : 4.88/5 ( download)

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Book Synopsis Encyclopedia of Machine Learning by : Claude Sammut

Download or read book Encyclopedia of Machine Learning written by Claude Sammut and published by Springer Science & Business Media. This book was released on 2011-03-28 with total page 1061 pages. Available in PDF, EPUB and Kindle. Book excerpt: This comprehensive encyclopedia, in A-Z format, provides easy access to relevant information for those seeking entry into any aspect within the broad field of Machine Learning. Most of the entries in this preeminent work include useful literature references.

Spectral Feature Selection for Data Mining (Open Access)

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Publisher : CRC Press
ISBN 13 : 1439862109
Total Pages : 224 pages
Book Rating : 4.00/5 ( download)

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Book Synopsis Spectral Feature Selection for Data Mining (Open Access) by : Zheng Alan Zhao

Download or read book Spectral Feature Selection for Data Mining (Open Access) written by Zheng Alan Zhao and published by CRC Press. This book was released on 2011-12-14 with total page 224 pages. Available in PDF, EPUB and Kindle. Book excerpt: Spectral Feature Selection for Data Mining introduces a novel feature selection technique that establishes a general platform for studying existing feature selection algorithms and developing new algorithms for emerging problems in real-world applications. This technique represents a unified framework for supervised, unsupervised, and semisupervise

Computational Complexity

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Publisher : Springer
ISBN 13 : 9781461417996
Total Pages : 0 pages
Book Rating : 4.96/5 ( download)

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Book Synopsis Computational Complexity by : Robert A. Meyers

Download or read book Computational Complexity written by Robert A. Meyers and published by Springer. This book was released on 2011-10-19 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Complex systems are systems that comprise many interacting parts with the ability to generate a new quality of collective behavior through self-organization, e.g. the spontaneous formation of temporal, spatial or functional structures. These systems are often characterized by extreme sensitivity to initial conditions as well as emergent behavior that are not readily predictable or even completely deterministic. The recognition that the collective behavior of the whole system cannot be simply inferred from an understanding of the behavior of the individual components has led to the development of numerous sophisticated new computational and modeling tools with applications to a wide range of scientific, engineering, and societal phenomena. Computational Complexity: Theory, Techniques and Applications presents a detailed and integrated view of the theoretical basis, computational methods, and state-of-the-art approaches to investigating and modeling of inherently difficult problems whose solution requires extensive resources approaching the practical limits of present-day computer systems. This comprehensive and authoritative reference examines key components of computational complexity, including cellular automata, graph theory, data mining, granular computing, soft computing, wavelets, and more.

Computational Intelligence for Machine Learning and Healthcare Informatics

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Publisher : Walter de Gruyter GmbH & Co KG
ISBN 13 : 3110649276
Total Pages : 414 pages
Book Rating : 4.77/5 ( download)

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Book Synopsis Computational Intelligence for Machine Learning and Healthcare Informatics by : Rajshree Srivastava

Download or read book Computational Intelligence for Machine Learning and Healthcare Informatics written by Rajshree Srivastava and published by Walter de Gruyter GmbH & Co KG. This book was released on 2020-06-22 with total page 414 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents a variety of techniques designed to enhance and empower multi-disciplinary and multi-institutional machine learning research in healthcare informatics. It is intended to provide a unique compendium of current and emerging machine learning paradigms for healthcare informatics, reflecting the diversity, complexity, and depth and breadth of this multi-disciplinary area.

Artificial Intelligence and Bioinspired Computational Methods

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Publisher : Springer Nature
ISBN 13 : 3030519716
Total Pages : 655 pages
Book Rating : 4.11/5 ( download)

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Book Synopsis Artificial Intelligence and Bioinspired Computational Methods by : Radek Silhavy

Download or read book Artificial Intelligence and Bioinspired Computational Methods written by Radek Silhavy and published by Springer Nature. This book was released on 2020-08-08 with total page 655 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book gathers the refereed proceedings of the Artificial Intelligence and Bioinspired Computational Methods Section of the 9th Computer Science On-line Conference 2020 (CSOC 2020), held on-line in April 2020. Artificial intelligence and bioinspired computational methods now represent crucial areas of computer science research. The topics presented here reflect the current discussion on cutting-edge hybrid and bioinspired algorithms and their applications.

Feature Extraction

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Publisher : Springer
ISBN 13 : 3540354883
Total Pages : 765 pages
Book Rating : 4.88/5 ( download)

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Book Synopsis Feature Extraction by : Isabelle Guyon

Download or read book Feature Extraction written by Isabelle Guyon and published by Springer. This book was released on 2008-11-16 with total page 765 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is both a reference for engineers and scientists and a teaching resource, featuring tutorial chapters and research papers on feature extraction. Until now there has been insufficient consideration of feature selection algorithms, no unified presentation of leading methods, and no systematic comparisons.

Feature Selection for High-Dimensional Data

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Publisher : Springer
ISBN 13 : 3319218581
Total Pages : 147 pages
Book Rating : 4.88/5 ( download)

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Book Synopsis Feature Selection for High-Dimensional Data by : Verónica Bolón-Canedo

Download or read book Feature Selection for High-Dimensional Data written by Verónica Bolón-Canedo and published by Springer. This book was released on 2015-10-05 with total page 147 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book offers a coherent and comprehensive approach to feature subset selection in the scope of classification problems, explaining the foundations, real application problems and the challenges of feature selection for high-dimensional data. The authors first focus on the analysis and synthesis of feature selection algorithms, presenting a comprehensive review of basic concepts and experimental results of the most well-known algorithms. They then address different real scenarios with high-dimensional data, showing the use of feature selection algorithms in different contexts with different requirements and information: microarray data, intrusion detection, tear film lipid layer classification and cost-based features. The book then delves into the scenario of big dimension, paying attention to important problems under high-dimensional spaces, such as scalability, distributed processing and real-time processing, scenarios that open up new and interesting challenges for researchers. The book is useful for practitioners, researchers and graduate students in the areas of machine learning and data mining.