Two New Regression and Curve Fitting Techniques Using Numerical Methods

Abstract

Regression is a process to estimate the bond among variables. It is a statistical technique and is used as prediction with the curve fitting in machine learning, data science, economics, etc. Linear and Polynomial regression is widely used to fit a curve and forecasting result. In this exploration, we propose two new linear and non-linear regression techniques using the strategy of interpolation-extrapolation and bisection of numerical analysis. However, interpolation and extrapolation cannot be applied in regression because of over-fitting curve. In our paper, we have developed a technique to reduce the curve fitting that will enable the interpolation and extrapolation scheme to use in regression. Another procedure is to find out an equation of curve fitting in an optimal way using the Bisection Method. We also demonstrate the graphical presentations and comparison through all the occurring iterations.