Patent 5640492 Issued on June 17, 1997. Estimated Expiration Date: June 30, 2014. Estimated Expiration Date is calculated based on simple USPTO term provisions. It does not account for terminal disclaimers, term adjustments, failure to pay maintenance fees, or other factors which might affect the term of a patent.
A soft margin classifier and method are disclosed for processing input data of a training set into classes separated by soft margins adjacent optimal hyperplanes. Slack variables are provided, allowing erroneous or difficult data in the training set to be taken into account in determining the optimal hyperplane. Inseparable data in the training set are separated without removal of data obstructing separation by determining the optimal hyperplane having minimal number of erroneous classifications of the obstructing data. The parameters of the optimal hyperplane generated from the training set determine decision functions or separators for classifying empirical data.
Other References
Bottou et al, "Comparison of classifier methods: A case study in Handwritten digit recognition," Proc. of 12th IAPR Conf., Oct. 9-13, 1994, pp. 77-82
Schulmeister, B, "The piecewise linear classifier DIPOL92," Machine Learning:ECML-94. pp. 411-414
R. Courant and D. Hilbert, Methods of Mathematical Physics, Interscience: New York, pp. 122-141, 1953
D.G. Luenberger, Linear and Non-Linear Programming, Addison-Wesley: Reading, MA, pp. 326-330, 1984
V.N. Vapnik, Estimation of Dependencies Based on Empirical Data, Springer-Verlag: New York, pp. 355-367, 1982
M. Aizerman, E. Braverman, and L. Rozonoer, "Theoretical Foundations of The Potential Function Method in Pattern Recognition Learning", Automation and Remote Control, vol. 25, pp. 821-837, Jun. 1964
B.E. Boser, I. Goyon, and V.N. Vapnik, "A Training Algorithm For Optimal Margin Classifiers", Proceedings Of The 4-th Workshop of Computational Learning Theory, vol. 4, San Mateo, CA, Morgan Kaufman, 1992
Y. Le Cun, B. Boser, J. Denker, D. Henderson, R. Howard, W. Hubbard, and L. Jackel, "Handwritten Digit Recognition with a Back-Propagation Network", (D. Touretzky, Ed.), Advances In Neural Information Processing Systems, vol. 2, Morgan Kaufman, 1990
A.N. Refenes et al., "Stock Ranking: Neural Networks Vs. Multiple Linear Regression":, IEEE International Conf. on Neural Networks, vol. 3, San Francisco, CA, IEEE, pp. 1419-1426, 1993
M. Rebollo et al., "A Mixed Integer Programming Approach to Multi-Spectral Image Classification", Pattern Recognition, vol. 9, No. 1, Jan. 1977, pp. 47-51, 54-55, and 57
V. Uebele et al., "Extracting Fuzzy Rules From Pattern Classification Neural Networks", Proceedings From 1993 International Conference on Systems, Man and Cybernetics, Le Touquet, France, 17-20, Oct. 1993, vol. 2, pp. 578-583
C. Cortes et al., "Support-Vector Networks", Machine Learning, vol. 20, No. 3, Sep. 1995, pp. 273-29