A training algorithm for optimal margin classifiers
COLT '92 Proceedings of the fifth annual workshop on Computational learning theory
The nature of statistical learning theory
The nature of statistical learning theory
Generalization performance of support vector machines and other pattern classifiers
Advances in kernel methods
Structural risk minimization over data-dependent hierarchies
IEEE Transactions on Information Theory
Support vector machines: hype or hallelujah?
ACM SIGKDD Explorations Newsletter - Special issue on “Scalable data mining algorithms”
Hierarchical Learning in Polynomial Support Vector Machines
Machine Learning
Choosing Multiple Parameters for Support Vector Machines
Machine Learning
Learning to Predict the Leave-One-Out Error of Kernel Based Classifiers
ICANN '01 Proceedings of the International Conference on Artificial Neural Networks
Non-symmetric Support Vector Machines
IWANN '01 Proceedings of the 6th International Work-Conference on Artificial and Natural Neural Networks: Connectionist Models of Neurons, Learning Processes and Artificial Intelligence-Part I
Asymptotic behaviors of support vector machines with Gaussian kernel
Neural Computation
The subspace information criterion for infinite dimensional hypothesis spaces
The Journal of Machine Learning Research
Variable selection using svm based criteria
The Journal of Machine Learning Research
Radius margin bounds for support vector machines with the RBF kernel
Neural Computation
A Compression Approach to Support Vector Model Selection
The Journal of Machine Learning Research
Leave-One-Out Bounds for Support Vector Regression Model Selection
Neural Computation
Optimizing resources in model selection for support vector machine
Pattern Recognition
Analysis of SVM regression bounds for variable ranking
Neurocomputing
Minimum reference set based feature selection for small sample classifications
Proceedings of the 24th international conference on Machine learning
Rough set based 1-v-1 and 1-v-r approaches to support vector machine multi-classification
Information Sciences: an International Journal
A Multi-criteria Convex Quadratic Programming model for credit data analysis
Decision Support Systems
Applying genetic algorithms and support vector machines to the gene selection problem
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology - VIII Brazilian Symposium on Neural Networks
A Leave-One-Out Bound for ν-Support Vector Regression
ICCS '07 Proceedings of the 7th international conference on Computational Science, Part III: ICCS 2007
On the Stability and Bias-Variance Analysis of Kernel Matrix Learning
CAI '07 Proceedings of the 20th conference of the Canadian Society for Computational Studies of Intelligence on Advances in Artificial Intelligence
Classes of Kernels for Hit Definition in Compound Screening
ICAISC '08 Proceedings of the 9th international conference on Artificial Intelligence and Soft Computing
Separating hypersurfaces of SVMs in input spaces
Pattern Recognition Letters
Model selection for the LS-SVM. Application to handwriting recognition
Pattern Recognition
IJCNN'09 Proceedings of the 2009 international joint conference on Neural Networks
Towards incremental classifier fusion
Intelligent Data Analysis
An optimization on pictogram identification for the road-sign recognition task using SVMs
Computer Vision and Image Understanding
Optimized fixed-size kernel models for large data sets
Computational Statistics & Data Analysis
A study of tuning hyperparameters for support vector machines
ICCSA'03 Proceedings of the 2003 international conference on Computational science and its applications: PartI
Classifier complexity reduction by support vector pruning in kernel matrix learning
IWANN'07 Proceedings of the 9th international work conference on Artificial neural networks
Tuning L1-SVM hyperparameters with modified radius margin bounds and simulated annealing
IWANN'07 Proceedings of the 9th international work conference on Artificial neural networks
Analysis of the distance between two classes for tuning SVM hyperparameters
IEEE Transactions on Neural Networks
An effective method of pruning support vector machine classifiers
IEEE Transactions on Neural Networks
GMRVVm-SVR model for financial time series forecasting
Expert Systems with Applications: An International Journal
Adapting decision DAGs for multipartite ranking
ECML PKDD'10 Proceedings of the 2010 European conference on Machine learning and knowledge discovery in databases: Part III
Simultaneous feature selection and parameters optimization for SVM by immune clonal algorithm
ICNC'05 Proceedings of the First international conference on Advances in Natural Computation - Volume Part II
PSO-Based hyper-parameters selection for LS-SVM classifiers
ICONIP'06 Proceedings of the 13th international conference on Neural Information Processing - Volume Part II
ISNN'05 Proceedings of the Second international conference on Advances in Neural Networks - Volume Part I
Linear program algorithm for estimating the generalization performance of SVM
ICNC'06 Proceedings of the Second international conference on Advances in Natural Computation - Volume Part II
Support vector classification with nominal attributes
CIS'05 Proceedings of the 2005 international conference on Computational Intelligence and Security - Volume Part I
Multi-objective parameters selection for SVM classification using NSGA-II
ICDM'06 Proceedings of the 6th Industrial Conference on Data Mining conference on Advances in Data Mining: applications in Medicine, Web Mining, Marketing, Image and Signal Mining
Feature selection using SVM probabilistic outputs
ICONIP'06 Proceedings of the 13 international conference on Neural Information Processing - Volume Part I
Environmental sounds classification based on visual features
CIARP'11 Proceedings of the 16th Iberoamerican Congress conference on Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications
A parsimony fuzzy rule-based classifier using axiomatic fuzzy set theory and support vector machines
Information Sciences: an International Journal
Nyström approximate model selection for LSSVM
PAKDD'12 Proceedings of the 16th Pacific-Asia conference on Advances in Knowledge Discovery and Data Mining - Volume Part I
Review: Supervised classification and mathematical optimization
Computers and Operations Research
Artificial Intelligence in Medicine
International Journal of Speech Technology
Fast pruning superfluous support vectors in SVMs
Pattern Recognition Letters
Computers and Electronics in Agriculture
Multiple spectral kernel learning and a gaussian complexity computation
Neural Computation
A nested heuristic for parameter tuning in Support Vector Machines
Computers and Operations Research
Pairwise FCM based feature weighting for improved classification of vertebral column disorders
Computers in Biology and Medicine
| Hi-index | 0.00 |
We introduce the concept of span of support vectors (SV) and show that the generalization ability of support vector machines (SVM) depends on this new geometrical concept. We prove that the value of the span is always smaller (and can be much smaller) than the diameter of the smallest sphere containing the support vectors, used in previous bounds (Vapnik, 1998). We also demonstate experimentally that the prediction of the test error given by the span is very accurate and has direct application in model selection (choice of the optimal parameters of the SVM).