SVM and Kernel Methods Matlab Toolbox. Key Features: SVM Classification using linear and quadratic penalization of misclassified examples ( penalization coefficients can be different for each examples); SVM Classification with Nearest Point Algorithm; Multiclass SVM : one against all, one against one and M-SVM; Large Scale SVM Classification/Regression; SVM epsilon and nu regression; One-Class SVM; Regularisation Networks; SVM bounds (Span estimate, radius/margin); Wavelet Kernel; SVM Based Feature Selection; Kernel PCA; Kernel Discriminant Analysis; SVM Based Feature selection; SVM AUC Optimization (Ranking SVM, ROC SVM) and RankBoost; Kernel Basis Pursuit and Least Angle Regression (LARS) Algorithm; Wavelet Kernel Regression with backfitting; Interface with a version of libsvm.

References in zbMATH (referenced in 20 articles )

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  1. Li, Jian-Hui; Wang, Fang; Li, Jin-Wei; Zou, Rui-Biao; Liao, Gui-Ping: Multifractal methods for rapeseed nitrogen nutrition qualitative diagnosis modeling (2016)
  2. Bouveyron, C.; Fauvel, M.; Girard, S.: Kernel discriminant analysis and clustering with parsimonious Gaussian process models (2015)
  3. De Vito, Ernesto; Rosasco, Lorenzo; Toigo, Alessandro: Learning sets with separating kernels (2014)
  4. Ma, Andy J.; Yuen, Pong C.: Reduced analytic dependency modeling: robust fusion for visual recognition (2014)
  5. Micheletti, Natan; Foresti, Loris; Robert, Sylvain; Leuenberger, Michael; Pedrazzini, Andrea; Jaboyedoff, Michel; Kanevski, Mikhail: Machine learning feature selection methods for landslide susceptibility mapping (2014)
  6. Toh, Kar-Ann; Tan, Geok-Choo: Exploiting the relationships among several binary classifiers via data transformation (2014)
  7. Song, Hyeongjin; Choi, K.K.; Lee, Ikjin; Zhao, Liang; Lamb, David: Adaptive virtual support vector machine for reliability analysis of high-dimensional problems (2013)
  8. Zhao, Jinwei; Yan, Guirong; Feng, Boqin; Mao, Wentao; Bai, Junqing: An adaptive support vector regression based on a new sequence of unified orthogonal polynomials (2013)
  9. Kim, Youngsung; Toh, Kar-Ann; Teoh, Andrew Beng Jin; Eng, How-Lung; Yau, Wei-Yun: An online AUC formulation for binary classification (2012)
  10. Kwak, Nojun: Kernel discriminant analysis for regression problems (2012)
  11. Hu, Yonggang; Wang, Yong; Wu, Yi; Li, Qiang; Hou, Chenping: Generalized mahalanobis depth in the reproducing kernel Hilbert space (2011)
  12. Jin, Xin; Gupta, Shalabh; Mukherjee, Kushal; Ray, Asok: Wavelet-based feature extraction using probabilistic finite state automata for pattern classification (2011)
  13. Ozer, Sedat; Chen, Chi H.; Cirpan, Hakan A.: A set of new Chebyshev kernel functions for support vector machine pattern classification (2011)
  14. Cruz-Cano, Raul; Chew, David S.H.; Choi, Kwok-Pui; Leung, Ming-Ying: Least-squares support vector machine approach to viral replication origin prediction (2010)
  15. de Leone, R.; Lazzari, C.: Error bounds for support vector machines with application to the identification of active constraints (2010)
  16. Fu, Si-Yao; Yang, Guo-Sheng; Hou, Zeng-Guang: Image category learning and classification via optimal linear combination of multiple partially matching kernels (2010) ioport
  17. Fennander, Henri; Kyrki, Ville; Fellman, Anna; Salminen, Antti; Kälviäinen, Heikki: Visual measurement and tracking in laser hybrid welding (2009) ioport
  18. Montuori, Alfonso; Raimondo, Giovanni; Pasero, Eros: An information theoretic approach for improving data driven prediction of protein model quality (2008)
  19. Mu, Tingting; Nandi, Asoke K.: Breast cancer detection from FNA using SVM with different parameter tuning systems and SOM-RBF classifier (2007)
  20. Basak, Jayanta: Online adaptive decision trees: pattern classification and function approximation (2006)