Computational Methods of Feature Selection

Computational Methods of Feature Selection PDF Author: Huan Liu
Publisher: CRC Press
ISBN: 1584888792
Category : Business & Economics
Languages : en
Pages : 437

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Book Description
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 Methods of Feature Selection

Computational Methods of Feature Selection PDF Author: Huan Liu
Publisher: CRC Press
ISBN: 1584888792
Category : Business & Economics
Languages : en
Pages : 437

Get Book Here

Book Description
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

Computational Intelligence and Feature Selection PDF Author: Richard Jensen
Publisher: John Wiley & Sons
ISBN: 0470377917
Category : Computers
Languages : en
Pages : 357

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Book Description
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.

Spectral Feature Selection for Data Mining

Spectral Feature Selection for Data Mining PDF Author: Zheng Alan Zhao
Publisher: CRC Press
ISBN: 1439862109
Category : Business & Economics
Languages : en
Pages : 220

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Book Description
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 Intelligence for Machine Learning and Healthcare Informatics

Computational Intelligence for Machine Learning and Healthcare Informatics PDF Author: Rajshree Srivastava
Publisher: Walter de Gruyter GmbH & Co KG
ISBN: 3110648199
Category : Computers
Languages : en
Pages : 348

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Book Description
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.

Feature Engineering and Selection

Feature Engineering and Selection PDF Author: Max Kuhn
Publisher: CRC Press
ISBN: 1351609467
Category : Business & Economics
Languages : en
Pages : 266

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Book Description
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.

Feature Selection for Data and Pattern Recognition

Feature Selection for Data and Pattern Recognition PDF Author: Urszula Stańczyk
Publisher: Springer
ISBN: 9783662508459
Category : Technology & Engineering
Languages : en
Pages : 0

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Book Description
This research book provides the reader with a selection of high-quality texts dedicated to current progress, new developments and research trends in feature selection for data and pattern recognition. Even though it has been the subject of interest for some time, feature selection remains one of actively pursued avenues of investigations due to its importance and bearing upon other problems and tasks. This volume points to a number of advances topically subdivided into four parts: estimation of importance of characteristic features, their relevance, dependencies, weighting and ranking; rough set approach to attribute reduction with focus on relative reducts; construction of rules and their evaluation; and data- and domain-oriented methodologies.

Feature Extraction

Feature Extraction PDF Author: Isabelle Guyon
Publisher: Springer
ISBN: 3540354883
Category : Computers
Languages : en
Pages : 765

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Book Description
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.

Computational Complexity

Computational Complexity PDF Author: Robert A. Meyers
Publisher: Springer
ISBN: 9781461417996
Category : Computers
Languages : en
Pages : 0

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Book Description
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.

Feature Selection for High-Dimensional Data

Feature Selection for High-Dimensional Data PDF Author: Verónica Bolón-Canedo
Publisher: Springer
ISBN: 3319218581
Category : Computers
Languages : en
Pages : 163

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Book Description
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.

Encyclopedia of Machine Learning

Encyclopedia of Machine Learning PDF Author: Claude Sammut
Publisher: Springer Science & Business Media
ISBN: 0387307680
Category : Computers
Languages : en
Pages : 1061

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Book Description
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.