A Support Vector Machine with a Hybrid Kernel and Minimal Vapnik-Chervonenkis Dimension

Mathematics

• Support Vector Machine 100%
• Vapnik-Chervonenkis Dimension 100%
• Upper Bound 40%
• Polynomial 20%
• Sufficient Condition 20%
• Neural Network 20%
• Basis Function 20%
• Test Data 20%
• Structural Risk Minimization 20%
• Dimensional Feature Space 20%
• Hyperplane 20%

Computer Science

• Support Vector Machine 100%
• Kernel Function 75%
• Experimental Result 25%
• Radial Basis Function 25%
• Optimization Criterion 25%
• Layer Neural Network 25%
• Sufficient Condition 25%
• Separating Hyperplane 25%
• Dimensional Feature Space 25%
• Risk Minimization 25%
• Machine Learning 25%