Support vector machines for classification and regression.

Keywords

Support vector machine, Outlier, Computer science, Least squares support vector machine, Radial basis function

References

• Chemometrics for Pattern RecognitionRichard G. Brereton — 2009
• Support Vector Machines for Pattern Classification重夫 阿部 — 1999
• Chemometrics: Data Analysis for the Laboratory and Chemical PlantRichard G. Brereton — 2003
• A tutorial on support vector regressionAlex Smola, Bernhard Schölkopf — 2004
• Active learning support vector machines for optimal sample selection in classificationSimeone Zomer, Miguel del Nogal Sánchez, Richard G. Brereton — 2004
• Support Vector Data DescriptionDavid M. J. Tax, Robert P. W. Duin — 2004
• Self Organising Maps for distinguishing polymer groups using thermal response curves obtained by dynamic mechanical analysis.Gavin R. Lloyd, Richard G. Brereton, John C. Duncan — 2008
• Comparison of performance of five common classifiers represented as boundary methods: Euclidean Distance to Centroids, Linear Discriminant Analysis, Quadratic Discriminant Analysis, Learning Vector Quantization and Support Vector Machines, as dependent on data structureSarah J. Dixon, Richard G. Brereton — 2009
• Support vector machines for face recognitionGuodong Guo, Stan Z. Li, Kap Luk Chan — 2001
• Pattern recognition and feature selection for the discrimination between grades of commercial plasticsBozena M. Lukasiak, Simeone Zomer, Richard G. Brereton — 2007
• Learning Vector Quantization for Multiclass Classification: Application to Characterization of PlasticsGavin R. Lloyd, Richard G. Brereton, Rita Faria — 2007
• THE USE OF MULTIPLE MEASUREMENTS IN TAXONOMIC PROBLEMSRonald Aylmer Fisher — 1936
• Cross-Validatory Estimation of the Number of Components in Factor and Principal Components ModelsSvante Wold — 1978
• Visualisation and interpretation of Support Vector Regression models.Bülent Üstün, W.J. Melssen, L.M.C. Buydens — 2007
• Multilevel multifactor designs for multivariate calibrationRichard G. Brereton — 1997
• Comparing support vector machines to PLS for spectral regression applicationsUwe Thissen, Mlh Michel Pepers, Bülent Üstün — 2004
• Pattern recognition for the analysis of polymeric materials.Bozena M. Lukasiak, Rita Faria, Simeone Zomer — 2006
• Support Vector Machines: A Recent Method for Classification in ChemometricsYun Xu, Simeone Zomer, Richard G. Brereton — 2006
• Modified support vector machines in financial time series forecastingFrancis E. H. Tay, Leilei Cao — 2002
• Dynamic mechanical analysis and chemometrics for polymer identificationRita Faria, John C. Duncan, Richard G. Brereton — 2007

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• In ovo sexing of chicken eggs by fluorescence spectroscopy哲志 外井 — 2017
• Breast cancer detection using deep convolutional neural networks and support vector machines吉文 寳田, 匠 三好, 千浩 平田 — 2019
• True Efficient Frontiers in Production Performance Assessment Using Machine Learning and Data Envelopment AnalysisKerry R. Poitier — 2010
• Multi-label feature selection with application to musical instrument recognitionTrudie Sandrock — 2013
• Finding the best statistical model to predict customer defection in telecommunication retail settingNkululeko Ngcongo — 2014
• Adaptive surrogate models for reliability analysis and reliability-based design optimizationVincent Dubourg — 2011
• MODÈLES DE SUBSTITUTION POUR L'OPTIMISATION GLOBALE DE FORME EN AÉRODYNAMIQUE ET MÉTHODE LOCALE SANS PARAMÉTRISATIONManuel Bompard — 2011
• Development of advanced algorithms to detect, characterize and forecast solar activitiesYuan Yuan — 2011
• The EEG of the neonatal brain : classification of background activityJohan Löfhede — 2009
• Automatic documents summarization using ontology based methodologiesAbdullah Bawakid — 2011
• SVM-based supervised and unsupervised classification schemesLuminiţa State, Iuliana Paraschiv-Munteanu — 2010
• Efficient Classification and Prediction Algorithms for Biomedical InformationRania Kilany — 2013
• Decoding Cognitive States from fMRI Data Using Support Vector RegressionMaria Grazia Di Bono, Marco Zorzi — 2008
• Modeling Novelty and Feature Combination using Support Vector Regression for Update SummarizationPraveen Bysani, Vijay Bharat, Vasudeva Varma — 2009
• Recent Trends in Text Classification TechniquesNidhi Nidhi, Vishal Gupta — 2011
• Computational Optimal Design and Uncertainty Quantification of Complex Systems Using Explicit Decision BoundariesAnirban Basudhar — 2011
• Dual-sensor fusion for seamless indoor user localisation and trackingMilan Redzic — 2013
• Predictive quantification of surrogate model fidelity based on modal variations with sample densityAli Mehmani, Souma Chowdhury, Achille Messac — 2015

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