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 30 articles )

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  1. Sussner, Peter; Campiotti, Israel: Extreme learning machine for a new hybrid morphological/linear perceptron (2020)
  2. Hwang, Kyoungmi; Kim, Dohyun; Lee, Kyungsik; Lee, Chungmok; Park, Sungsoo: Embedded variable selection method using signomial classification (2017)
  3. Xiao, Yancai; Wang, Yujia; Mu, Huan; Kang, Na: Research on misalignment fault isolation of wind turbines based on the mixed-domain features (2017)
  4. Li, Jian-Hui; Wang, Fang; Li, Jin-Wei; Zou, Rui-Biao; Liao, Gui-Ping: Multifractal methods for rapeseed nitrogen nutrition qualitative diagnosis modeling (2016)
  5. Bouveyron, C.; Fauvel, M.; Girard, S.: Kernel discriminant analysis and clustering with parsimonious Gaussian process models (2015)
  6. Luss, Ronny; D’Aspremont, Alexandre: Predicting abnormal returns from news using text classification (2015)
  7. Wang, Shijun; Li, Diana; Petrick, Nicholas; Sahiner, Berkman; Linguraru, Marius George; Summers, Ronald M.: Optimizing area under the ROC curve using semi-supervised learning (2015)
  8. De Vito, Ernesto; Rosasco, Lorenzo; Toigo, Alessandro: Learning sets with separating kernels (2014)
  9. Huang, Xiaolin; Shi, Lei; Suykens, Johan A. K.: Asymmetric least squares support vector machine classifiers (2014)
  10. Ma, Andy J.; Yuen, Pong C.: Reduced analytic dependency modeling: robust fusion for visual recognition (2014)
  11. Micheletti, Natan; Foresti, Loris; Robert, Sylvain; Leuenberger, Michael; Pedrazzini, Andrea; Jaboyedoff, Michel; Kanevski, Mikhail: Machine learning feature selection methods for landslide susceptibility mapping (2014)
  12. Toh, Kar-Ann; Tan, Geok-Choo: Exploiting the relationships among several binary classifiers via data transformation (2014)
  13. Wang, Fang; Zou, Rui-Biao; Liao, Gui-Ping; Li, Jin-Wei; Liu, Zi-Qiang: Local multifractal detrended fluctuation analysis for tea breeds identification (2014)
  14. Song, Hyeongjin; Choi, K. K.; Lee, Ikjin; Zhao, Liang; Lamb, David: Adaptive virtual support vector machine for reliability analysis of high-dimensional problems (2013)
  15. 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)
  16. Kim, Youngsung; Toh, Kar-Ann; Teoh, Andrew Beng Jin; Eng, How-Lung; Yau, Wei-Yun: An online AUC formulation for binary classification (2012)
  17. Kwak, Nojun: Kernel discriminant analysis for regression problems (2012)
  18. Foresti, Loris; Tuia, Devis; Kanevski, Mikhail; Pozdnoukhov, Alexei: Learning wind fields with multiple kernels (2011)
  19. Hua, Lin; Zhou, Ping; Liu, Hong; Li, Lin; Yang, Zheng; Liu, Zhi-cheng: Mining susceptibility gene modules and disease risk genes from SNP data by combining network topological properties with support vector regression (2011)
  20. Hu, Yonggang; Wang, Yong; Wu, Yi; Li, Qiang; Hou, Chenping: Generalized Mahalanobis depth in the reproducing kernel Hilbert space (2011)

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