Effect of Various Kernels and Feature Selection Methods on SVM Performance for Detecting Email Spams
Shrawan Kumar Trivedi · 2013
This Research presents the effects of interaction between various Kernel functions and different Feature Selection Techniques for improving the learning capability of Support Vector Machine (SVM) in detecting email spams. The interaction of four Kernel functions of SVM i.e. “Normalised Polynomial Kernel (NP)”, “Polynomial Kernel (PK)”, “Radial Basis Function Kernel (RBF)”, and “Pearson VII Function-Based Universal Kernel (PUK) ” with three feature selection