Support Vector Machines Applications (82 results)
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- Softcover
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- Hardcover
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- Softcover
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Taschenbuch. Condition: Neu. Support Vector Machines and Particle Swarm Optimization | Applications to Reliability Prediction | Isis Didier Lins (u. a.) | Taschenbuch | 92 S. | Englisch | 2010 | LAP LAMBERT Academic Publishing | EAN 9783838319407 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19,… 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.
- Softcover
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Taschenbuch. Condition: Neu. Human Face Recognition with Support Vector Machines | Algorithms and Applications | Latha Parthiban | Taschenbuch | Einband - flex.(Paperback) | Englisch | 2011 | VDM Verlag Dr. Müller | EAN 9783639366990 | Verantwortliche Person für die EU: OmniScriptum GmbH & Co. KG, Bahnhofstr. 28, 66111 Saarbrück…en, info[at]akademikerverlag[dot]de | Anbieter: preigu.
Language: English
Published by Springer, 2018
Series: Book 180 of 538 - Studies in Computational Intelligence
- Softcover
Seller: Ria Christie Collections, Uxbridge, United KingdomRia Christie Collections
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Language: English
Published by Springer, 2016
Series: Book 180 of 538 - Studies in Computational Intelligence
- Hardcover
Seller: Studibuch, Stuttgart, GermanyStudibuch
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- Softcover
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Language: English
Published by Springer, 2018
Series: Book 180 of 538 - Studies in Computational Intelligence
- Softcover
Seller: Books Puddle, New York, NY, U.S.A.Books Puddle
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Language: English
Published by Wiley-Interscience, 2009
Series: Book 2 of 7 - Wiley Series on Methods and Applications in Data Mining
- Hardcover
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- Softcover
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- Softcover
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- Hardcover
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- Hardcover
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- Hardcover
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Language: English
Published by Springer, 2018
Series: Book 180 of 538 - Studies in Computational Intelligence
- Softcover
Seller: preigu, Osnabrück, Germanypreigu
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Taschenbuch. Condition: Neu. Twin Support Vector Machines | Models, Extensions and Applications | Jayadeva (u. a.) | Taschenbuch | xiv | Englisch | 2018 | Springer | EAN 9783319834627 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbiete…r: preigu.
Language: English
Published by Springer International Publishing, Springer International Publishing, 2018
Series: Book 180 of 538 - Studies in Computational Intelligence
- Softcover
Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH
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Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book provides a systematic and focused study of the various aspects of twin support vector machines (TWSVM) and related developments for classification and regression. In addition to presenting most of the basic models of TWSVM and twin suppor…t vector regression (TWSVR) available in the literature, it also discusses the important and challenging applications of this new machine learning methodology. A chapter on 'Additional Topics' has been included to discuss kernel optimization and support tensor machine topics, which are comparatively new but have great potential in applications. It is primarily written for graduate students and researchers in the area of machine learning and related topics in computer science, mathematics, electrical engineering, management science and finance.
Language: English
Published by Springer, Springer, 2016
Series: Book 180 of 538 - Studies in Computational Intelligence
- Hardcover
Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH
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US$ 127.38
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Buch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book provides a systematic and focused study of the various aspects of twin support vector machines (TWSVM) and related developments for classification and regression. In addition to presenting most of the basic models of TWSVM and twin support vecto…r regression (TWSVR) available in the literature, it also discusses the important and challenging applications of this new machine learning methodology. A chapter on 'Additional Topics' has been included to discuss kernel optimization and support tensor machine topics, which are comparatively new but have great potential in applications. It is primarily written for graduate students and researchers in the area of machine learning and related topics in computer science, mathematics, electrical engineering, management science and finance.
- Hardcover
Seller: Buchpark, Trebbin, GermanyBuchpark
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Condition: Hervorragend. Zustand: Hervorragend | Seiten: 320 | Sprache: Englisch | Produktart: Bücher | This book contains select chapters on support vector algorithms from different perspectives, including mathematical background, properties of various kernel functions, and several applications. The main focus of this book is o…n orthogonal kernel functions, and the properties of the classical kernel functions¿Chebyshev, Legendre, Gegenbauer, and Jacobi¿are reviewed in some chapters. Moreover, the fractional form of these kernel functions is introduced in the same chapters, and for ease of use for these kernel functions, a tutorial on a Python package named ORSVM is presented. The book also exhibits a variety of applications for support vector algorithms, and in addition to the classification, these algorithms along with the introduced kernel functions are utilized for solving ordinary, partial, integro, and fractional differential equations.On the other hand, nowadays, the real-time and big data applications of support vector algorithms are growing. Consequently, the Compute Unified Device Architecture (CUDA) parallelizing the procedure of support vector algorithms based on orthogonal kernel functions is presented. The book sheds light on how to use support vector algorithms based on orthogonal kernel functions in different situations and gives a significant perspective to all machine learning and scientific machine learning researchers all around the world to utilize fractional orthogonal kernel functions in their pattern recognition or scientific computing problems.
- Hardcover
Seller: Buchpark, Trebbin, GermanyBuchpark
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Condition: Sehr gut. Zustand: Sehr gut | Seiten: 312 | Sprache: Englisch | Produktart: Bücher | Support vector machines (SVM) have both a solid mathematical background and practical applications. This book focuses on the recent advances and applications of the SVM, such as image processing, medical practice, computer vision, and… pattern recognition, machine learning, applied statistics, and artificial intelligence. The aim of this book is to create a comprehensive source on support vector machine applications.
- Hardcover
Seller: Ria Christie Collections, Uxbridge, United KingdomRia Christie Collections
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- Softcover
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- Hardcover
Seller: Books Puddle, New York, NY, U.S.A.Books Puddle
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- Softcover
Seller: preigu, Osnabrück, Germanypreigu
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Taschenbuch. Condition: Neu. Learning with Fractional Orthogonal Kernel Classifiers in Support Vector Machines | Theory, Algorithms and Applications | Jamal Amani Rad (u. a.) | Taschenbuch | xiv | Englisch | 2024 | Springer | EAN 9789811965555 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 He…idelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
- Softcover
Seller: Buchpark, Trebbin, GermanyBuchpark
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Condition: Hervorragend. Zustand: Hervorragend | Seiten: 319 | Sprache: Englisch | Produktart: Bücher | This book contains select chapters on support vector algorithms from different perspectives, including mathematical background, properties of various kernel functions, and several applications. The main focus of this book is o…n orthogonal kernel functions, and the properties of the classical kernel functions¿Chebyshev, Legendre, Gegenbauer, and Jacobi¿are reviewed in some chapters. Moreover, the fractional form of these kernel functions is introduced in the same chapters, and for ease of use for these kernel functions, a tutorial on a Python package named ORSVM is presented. The book also exhibits a variety of applications for support vector algorithms, and in addition to the classification, these algorithms along with the introduced kernel functions are utilized for solving ordinary, partial, integro, and fractional differential equations.On the other hand, nowadays, the real-time and big data applications of support vector algorithms are growing. Consequently, the Compute Unified Device Architecture (CUDA) parallelizing the procedure of support vector algorithms based on orthogonal kernel functions is presented. The book sheds light on how to use support vector algorithms based on orthogonal kernel functions in different situations and gives a significant perspective to all machine learning and scientific machine learning researchers all around the world to utilize fractional orthogonal kernel functions in their pattern recognition or scientific computing problems.
