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Support vector machines applications [electronic resource]

Support vector machines applications [electronic resource]

Material type
E-Book(소장)
Personal Author
Ma, Yunqian. Guo, Guodong.
Title Statement
Support vector machines applications [electronic resource] / Yunqian Ma, Guodong Guo, editors.
Publication, Distribution, etc
Cham :   Springer International Publishing :   Imprint: Springer,   2014.  
Physical Medium
1 online resource (vii, 302 p.) : ill. (some col.).
ISBN
9783319023007
요약
Support vector machines (SVM) have both a solid mathematical background and good performance in practical applications. This book focuses on the recent advances and applications of the SVM in different areas, such as image processing, medical practice, computer vision, pattern recognition, machine learning, applied statistics, business intelligence, and artificial intelligence. The aim of this book is to create a comprehensive source on support vector machine applications, especially some recent advances.
General Note
Title from e-Book title page.  
Content Notes
Augmented-SVM for gradient observations with application to learning multiple-attractor dynamics -- Multi-class Support Vector Machine -- Novel Inductive and Transductive Transfer Learning Approaches Based on Support Vector Learning -- Security Evaluation of Support Vector Machines in Adversarial Environments -- Application of SVMs to the Bag-of-features Model— A Kernel Perspective -- Support Vector Machines for Neuroimage Analysis: Interpretation from Discrimination -- Kernel Machines for Imbalanced Data Problem and the Use in Biomedical Applications -- Soft Biometrics from Face Images using Support Vector Machines.
Bibliography, Etc. Note
Includes bibliographical references.
이용가능한 다른형태자료
Issued also as a book.  
Subject Added Entry-Topical Term
Support vector machines. Supervised learning (Machine learning).
Short cut
URL
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020 ▼a 9783319023007
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050 0 0 ▼a Q325.5
082 0 4 ▼a 006.31 ▼2 23
084 ▼a 006.31 ▼2 DDCK
090 ▼a 006.31
245 0 0 ▼a Support vector machines applications ▼h [electronic resource] / ▼c Yunqian Ma, Guodong Guo, editors.
260 ▼a Cham : ▼b Springer International Publishing : ▼b Imprint: Springer, ▼c 2014.
300 ▼a 1 online resource (vii, 302 p.) : ▼b ill. (some col.).
500 ▼a Title from e-Book title page.
504 ▼a Includes bibliographical references.
505 0 ▼a Augmented-SVM for gradient observations with application to learning multiple-attractor dynamics -- Multi-class Support Vector Machine -- Novel Inductive and Transductive Transfer Learning Approaches Based on Support Vector Learning -- Security Evaluation of Support Vector Machines in Adversarial Environments -- Application of SVMs to the Bag-of-features Model— A Kernel Perspective -- Support Vector Machines for Neuroimage Analysis: Interpretation from Discrimination -- Kernel Machines for Imbalanced Data Problem and the Use in Biomedical Applications -- Soft Biometrics from Face Images using Support Vector Machines.
520 ▼a Support vector machines (SVM) have both a solid mathematical background and good performance in practical applications. This book focuses on the recent advances and applications of the SVM in different areas, such as image processing, medical practice, computer vision, pattern recognition, machine learning, applied statistics, business intelligence, and artificial intelligence. The aim of this book is to create a comprehensive source on support vector machine applications, especially some recent advances.
530 ▼a Issued also as a book.
538 ▼a Mode of access: World Wide Web.
650 0 ▼a Support vector machines.
650 0 ▼a Supervised learning (Machine learning).
700 1 ▼a Ma, Yunqian.
700 1 ▼a Guo, Guodong.
856 4 0 ▼u https://oca.korea.ac.kr/link.n2s?url=http://dx.doi.org/10.1007/978-3-319-02300-7
945 ▼a KLPA
991 ▼a E-Book(소장)

Holdings Information

No. Location Call Number Accession No. Availability Due Date Make a Reservation Service
No. 1 Location Main Library/e-Book Collection/ Call Number CR 006.31 Accession No. E14034184 Availability Loan can not(reference room) Due Date Make a Reservation Service M

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