Transcription of Support Vector Machines for Classification and …
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Support Vector Machines for Classification and …
ISIS Technical Report Support Vector Machines for Classification and regression Steve Gunn 14 May 1998. Contents 1 Introduction 5. Statistical Learning Theory ..6. VC .. 7. Structural Risk Minimisation .. 7. 2 Support Vector Classification 9. The Optimal Separating Hyperplane ..9. Linearly Separable Example .. 13. The Generalised Optimal Separating Hyperplane ..14. Linearly Non-Separable Example .. 16. Generalisation in High Dimensional Feature Space ..17. Polynomial Mapping 19. 3 Feature Space 21. Kernel Polynomial .. 21. Gaussian Radial Basis 21. Exponential Radial Basis Function .. 22. Multi-Layer 22. Fourier Series .. 22. 22. B splines .. 23. Additive Kernels .. 23. Tensor Product 23. Implicit vs. Explicit Bias ..23. Data Normalisation ..24. Kernel Selection ..24. 4 Classification Example: IRIS data 25. Applications ..28. 5 Support Vector regression 31. Linear -Insensitive Loss Function.
ISIS Technical Report Support Vector Machines for Classification and Regression Steve Gunn 14 May 1998
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