In the last few years, various types of machine learning algorithms, such as Support Vector Machine (SVM), Regression (SVR), and Non-negative Matrix Factorization (NMF) have been introduced. The kernel approach is an effective method for increasing classification accuracy algorithms. This paper introduces a family one-parameter functions improving SVM classification. proposed function consists ...

We present a new barrier function, based on a kernel function with a linear growth term and an inverse linear barrier term. Existing kernel functions have a quadratic (or higher degree) growth term, and a barrier term that is either transcendent (e.g. logarithmic) or of a more complicated algebraic form. So the new kernel function has the simplest possible form compared with all existing kernel...