SVM-based supervised and unsupervised classification schemes

Keywords

Support vector machine, Computer science, Artificial intelligence, Kernel (algebra), Pattern recognition (psychology)

References

• Multi-class support vector machine classifier in EMG diagnosisGurmanik Kaur, Ajat Shatru Arora, Vibha Jain — 2009
• Support Vector Machines for Pattern Classification重夫 阿部 — 1999
• Pattern Recognition and Machine LearningChris Bishop — 2006
• Learning with Kernels: support vector machines, regularization, optimization, and beyondBernhard Schölkopf, Alexander J. Smola — 2001
• Learning with Kernels: Support Vector Machines, Regularization, Optimization, and BeyondChristopher K. I. Williams — 2003
• On Mercer's TheoremGen-ichirô Sunouchi — 1946
• Functions of Positive and Negative Type, and their Connection with the Theory of Integral EquationsJames W. Mercer — 1909
• Support vector machines for classification and regression.Richard G. Brereton, Gavin R. Lloyd — 2010
• Comparison studies on classification for remote sensing image based on data mining methodHang Xiao, Xiubin Zhang — 2008
• Support-Vector NetworksCorinna Cortes, Vladimir Vapnik — 1995
• Some methods for classification and analysis of multivariate observationsJames B. MacQueen — 1967
• Learning Kernel Classifiers: Theory and AlgorithmsRalf Herbrich — 2001
• A Tutorial on Support Vector Machines for Pattern RecognitionChristopher J. C. Burges — 1998
• Support Vector Machines: Theory and Applications (Studies in Fuzziness and Soft Computing)Lipo Wang — 2005
• The emotion recognition through classification with the support vector machinesZhi Teng, Fuji Ren, Shingo Kuroiwa — 2006
• Face recognition with co-training and ensemble-driven learningNeamat El Gayar, Shaban A. Shaban, Sayed Hamdy — 2007
• Statistical Learning TheoryYuhai Wu — 2021
• An Introduction to Support Vector Machines and Other Kernel-based Learning MethodsNello Cristianini, John Shawe‐Taylor — 2000
• Mercer's Theorem, Feature Maps, and SmoothingHà Quang Minh, Partha Niyogi, Yuan Yao — 2006
• A TUTORIAL ON SUPPORT VECTOR MACHINES FOR PATTERN RECOGNITION, DATA MINING AND KNOWLEDGE DISCOVERYBurger C.J.C. — 1998

Cited by

• A new case-based reasoning method based on dissimilar relationsNing Xiong — 2014
• Counterfeit Image Detection in Face Recognition Systems using Stereo Vision and Optical Flow MethodsMartha CEJUDO-TORRES-OROZCO, Elizabeh GARCIA-RIOS, E. Escamilla-Hernandez — 2014

Related papers

• The classification and recognition method of the Quasars based on K-C-SVMZhang Li, Chenjin Zhang, Qingyang Xu — 2017
• Parameter determination of support vector machine using scatter search approachMohammed H. Afif, Abdel-Rahman Hedar, Taysir H. Abdel Hamid — 2012
• Application of RS Theory and SVM in the Ore-Rock ClassificationDewen Seng, Wenlan Chen — 2009
• Gene Selection and Classification Using Non-linear Kernel Support Vector Machines Based on Gene Expression DataZhang Qizhong — 2007
• The Comparative Study of Classification Algorithm Based on Kernel methodsJianghong Chen — 2009
• Comparing the Performance of the Kernel Functions in the LDA-SVM Based Classification Algorithm in the LabVIEW EnvironmentDuygu Kaya, Mustafa Türk — 2018
• Performance Evaluation of Kernels in Support Vector MachineIntisar Al-Mejibli, Dhafar Hamed, Jwan K. Alwan — 2018
• Performance evaluation of support vector machine classification approaches in data miningS. Chidambaram, K. G. Srinivasagan — 2018
• Fast Support Vector Machine Classification for Large Data SetsXiaoou Li, Wen Yu — 2014
• Research on Kernel Function Selection Simulation Based on SVM ClassificationLiangjun Zhang — 2011