System Modeling using Predictor classes

System modeling has become one of the most actively researched fields in the last decade. This new-found interest in modeling of systems can be attributed to the impact it has as an inter-disciplinary concept as well as the increased need for optimized and intelligent modeling techniques for disruptive technologies such as machine learning, artificial intelligence and computer vision.This study proposes a generalized mathematical formula to frame a designated function (Target Function) with the help of an available function (Regressor Function) and predictor variables. Categorically, this research attempts to aid designers by providing a mathematical framework for them to substitute their datasets and obtain results thereby reducing the complexity of mathematical modeling required. Furthermore, the discussed design schematics have proved capable of modeling systems with algebraic, transcendental, stochastic behaviours. The necessary calculations and mathematical formulations have been tabulated and deliberated for the same.