SVMACHINE Procedure

References

  • Burges, C. J. C. (1998). “A Tutorial on Support Vector Machines for Pattern Recognition.” Data Mining and Knowledge Discovery 2:121–167.

  • Cristianini, N., and Shawe-Taylor, J. (2000). An Introduction to Support Vector Machines and Other Kernel-Based Learning Methods. New York: Cambridge University Press.

  • Gertz, E. M., and Griffin, J. D. (2005). Support Vector Machine Classifiers for Large Data Sets. Technical Report ANL/MCS-TM-289, Mathematics and Computer Science Division, Argonne National Laboratory.

  • Gertz, E. M., and Griffin, J. D. (2010). “Using an Iterative Linear Solver in an Interior-Point Method for Generating Support Vector Machines.” Computational Optimization and Applications 47:431–453.

  • Hsieh, C.-J., Chang, K.-W., Lin, C.-J., Keerthi, S. S., and Sundararajan, S. (2008). “A Dual Coordinate Descent Method for Large-Scale Linear SVM.” In Proceedings of the 25th International Conference on Machine Learning, 408–415. New York: ACM.

  • Smola, A. J., and Schölkopf, B. (2004). “A Tutorial on Support Vector Regression.” Statistics and Computing 14:199–222. https://doi.org/10.1023/B:STCO.0000035301.49549.88.

  • Vapnik, V. N. (1995). The Nature of Statistical Learning Theory. New York: Springer-Verlag.

Last updated: July 11, 2024