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2009, 1st ed., Wiley series on methods and applications in data mining, ISBN 0470371927, xv, 246
An easy-to-follow introduction to support vector machines This book provides an in-depth, easy-to-follow introduction to support vector machines drawing only... 
Support vector machines | Computer algorithms | Data mining | Machine learning | COMPUTERS / Databases / Data Mining
Book
ACM Transactions on Intelligent Systems and Technology (TIST), ISSN 2157-6904, 04/2011, Volume 2, Issue 3, pp. 1 - 27
LIBSVM is a library for Support Vector Machines (SVMs). We have been actively developing this package since the year 2000. The goal is to help users to easily... 
Classification LIBSVM optimization regression support vector machines SVM | Algorithms | WORKING SET SELECTION | COMPUTER SCIENCE, INFORMATION SYSTEMS | Experimentation | Performance | COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Journal Article
Physical Review Letters, ISSN 0031-9007, 09/2014, Volume 113, Issue 3, p. 130503
Supervised machine learning is the classification of new data based on already classified training examples. In this work, we show that the support vector... 
LOW-RANK APPROXIMATION | PHYSICS, MULTIDISCIPLINARY | ALGORITHMS | Training | Support vector machines | Algorithms | Data management | Mathematical analysis | Classification | Polynomials | Sampling
Journal Article
2011, ISBN 9781439821275, x, 201
"Support vector machines (SVMs), a promising machine learning method, is a powerful tool for chemical data analysis and for modeling complex physicochemical... 
Support vector machines | Chemometrics
Book
Pattern Recognition, ISSN 0031-3203, 2003, Volume 36, Issue 12, pp. 2757 - 2767
Even the support vector machine (SVM) has been proposed to provide a good generalization performance, the classification result of the practically implemented... 
Boosting | SVM ensemble | SVM | Iris and hand-written digit recognition | Fraud detection | Bagging | boosting | bagging | fraud detection | NETWORKS | iris and hand-written digit recognition | COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE | ENGINEERING, ELECTRICAL & ELECTRONIC
Journal Article
Mechanical Systems and Signal Processing, ISSN 0888-3270, 2007, Volume 21, Issue 6, pp. 2560 - 2574
Recently, the issue of machine condition monitoring and fault diagnosis as a part of maintenance system became global due to the potential advantages to be... 
Fault diagnosis | Support vector machine | Machine condition monitoring | SYSTEM | fault diagnosis | INDUCTION-MOTORS | ROTATING MACHINERY | machine condition monitoring | CLASSIFICATION | ENGINEERING, MECHANICAL | ARTIFICIAL NEURAL-NETWORKS | GENETIC ALGORITHMS | ROTOR | support vector machine | ROUGH SET | BEARING
Journal Article
Pattern Recognition, ISSN 0031-3203, 01/2013, Volume 46, Issue 1, pp. 305 - 316
In this paper, we proposed a new robust twin support vector machine (called ) via second order cone programming formulations for classification, which can deal... 
Twin support vector machine | Robust | Classification | Second order cone programming | REGRESSION | SELECTION | COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE | ENGINEERING, ELECTRICAL & ELECTRONIC | Support vector machines | Mathematical analysis | Cone classifiers | Programming | Inverse | Robustness | Pattern recognition
Journal Article
Knowledge-Based Systems, ISSN 0950-7051, 05/2013, Volume 43, pp. 74 - 81
It has been shown that the structural information of data may contain useful prior domain knowledge for training a classifier. How to apply the structural... 
Structural information of data | Twin support vector machine | Optimization | Classification | Machine learning | RECOGNITION | ROBUST | COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE | Analysis | Algorithms
Journal Article
Information Sciences, ISSN 0020-0255, 05/2016, Volume 343-344, pp. 79 - 93
Support vector machine (SVM) and Fisher discriminant analysis (FDA) are two commonly used methods in machine learning and pattern recognition. A combined... 
Support vector machine | Fisher discriminant analysis | Fisher regularization | Kernel trick | Maximum margin regularization | RELATIVE MARGIN | KERNEL | FRAMEWORK | COMPUTER SCIENCE, INFORMATION SYSTEMS | SVM | Learning | Support vector machines | Discriminant analysis | Approximation | Classification | Pattern recognition | Regularization | Joints
Journal Article
IEEE Transactions on Pattern Analysis and Machine Intelligence, ISSN 0162-8828, 05/2014, Volume 36, Issue 5, pp. 984 - 997
Journal Article
Neural Networks, ISSN 0893-6080, 12/2012, Volume 36, pp. 112 - 119
The Universum, which is defined as the sample not belonging to either class of the classification problem of interest, has been proved to be helpful in... 
Universum | Twin support vector machine | Classification | NEUROSCIENCES | COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE | Motion | Computer Systems | Image Processing, Computer-Assisted - methods | Support Vector Machine | Databases as Topic | Neural Networks (Computer)
Journal Article
Expert Systems With Applications, ISSN 0957-4174, 02/2015, Volume 42, Issue 2, pp. 741 - 750
Journal Article
IEEE Transactions on Neural Networks and Learning Systems, ISSN 2162-237X, 10/2015, Volume 26, Issue 10, pp. 2583 - 2588
Journal Article
Pattern Recognition Letters, ISSN 0167-8655, 03/2017, Volume 88, pp. 20 - 25
This paper studies the role of the sample mean in binary classifier based on the margin theory. Support Vector Machine (SVM) with maximized minimum margin is... 
Margin distribution | Sample mean | Minimum margin | Classification | REGRESSION | IMBALANCED DATA | COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Journal Article