Kernel-Based Nonparametric Regression Method

Regression is a basic statistical tool in data mining, which is to predict the relationship between a dependent variable and one or more independent variables. Parametric and nonparametric regression are two kinds of regression approach used for various problems. In this paper, we proposed a kernel-based nonparametric regression method, which can solve nonlinear regression problem properly by mapping the data to a higher-dimensional space by kernel function. With this method, we conducted a series of experiments on nonlinear function and real world regression problems, and the results reveal the effectiveness of the model.