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Support vector machines applications [electronic resource]

자료유형

E-Book(소장)

개인저자

Ma, Yunqian. Guo, Guodong.

서명 / 저자사항

Support vector machines applications [electronic resource] / Yunqian Ma, Guodong Guo, editors.

발행사항

Cham : Springer International Publishing : Imprint: Springer, 2014.

형태사항

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.

일반주기

Title from e-Book title page.

내용주기

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.

서지주기

Includes bibliographical references.

이용가능한 다른형태자료

Issued also as a book.

일반주제명

Support vector machines. Supervised learning (Machine learning).

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URL

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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)

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No.	소장처	청구기호	등록번호	도서상태	반납예정일	예약	서비스
No. 1	소장처 중앙도서관/e-Book 컬렉션/	청구기호 CR 006.31	등록번호 E14034184	도서상태 대출불가(열람가능)	반납예정일	예약	서비스 M

Support vector machines applications [electronic resource]

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