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Support vector machines : theory and applications

Support vector machines : theory and applications (Loan 20 times)

Material type
단행본
Personal Author
Wang, Lipo.
Title Statement
Support vector machines : theory and applications / Lipo Wang (ed.).
Publication, Distribution, etc
Berlin ;   New York :   Springer ,   c2005.  
Physical Medium
x, 431 p. : fig. (some col.), tab. ; 25 cm.
Series Statement
Studies in fuzziness and soft computing , 1434-9922 ; v. 177
ISBN
3540243887 (hd.bd.)
Bibliography, Etc. Note
Includes bibliographical references.
Subject Added Entry-Topical Term
Machine learning. Data mining. Pattern recognition systems.
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245 0 0 ▼a Support vector machines : ▼b theory and applications / ▼c Lipo Wang (ed.).
260 ▼a Berlin ; ▼a New York : ▼b Springer , ▼c c2005.
300 ▼a x, 431 p. : ▼b fig. (some col.), tab. ; ▼c 25 cm.
440 0 ▼a Studies in fuzziness and soft computing , ▼x 1434-9922 ; ▼v v. 177
504 ▼a Includes bibliographical references.
650 0 ▼a Machine learning.
650 0 ▼a Data mining.
650 0 ▼a Pattern recognition systems.
700 1 ▼a Wang, Lipo.
945 ▼a KINS

Holdings Information

No. Location Call Number Accession No. Availability Due Date Make a Reservation Service
No. 1 Location Science & Engineering Library/Sci-Info(Stacks2)/ Call Number 006.3 S959 Accession No. 121121633 Availability Available Due Date Make a Reservation Service B M

Contents information

Table of Contents

From the contents: Support Vector Machines - An Introduction.- Multiple Model Estimation for Nonlinear Classification.- Componentwise Least Squares Support Vector Machines.- Active Support Vector Learning with Statistical Queries.- Local Learning vs. Global Learning: An Introduction to Maxi-Min Margin Machine.- Active-Set Methods for Support Vector Machines.- Theoretical and Practical Model Selection Methods for Support Vector Classifiers.- Adaptive Discriminant and Quasiconformal Kernel Nearest Neighbor Classification.- Improving the Performance of the Support Vector Machine: Two Geometrical Scaling Methods.- An Accelerated Robust Support Vector Machine Algorithm.- Fuzzy Support Vector Machines with Automatic Membership Setting.- Iterative Single Data Algorithm for Training Kernel Machines from Huge Data Sets: Theory and Performance.- Kernel Discriminant Learning with Application to Face Recognition.- Fast Color Texture-based Object Detection in Images: Application to License Plate Localization.


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