Adjusted Overfitting Regression

TL;DR

This paper introduces a novel distance-based regression method designed to mitigate overfitting and underfitting, aiming to improve prediction accuracy through optimization and practical application on real data.

Contribution

The paper presents a new regression approach that adjusts for overfitting and underfitting using distance-based techniques, with demonstrated optimization and practical application.

Findings

Effective reduction of overfitting in regression models

Improved prediction accuracy demonstrated on real data

Optimization techniques enhance the regression method

Abstract

In this paper, I will introduce a new form of regression, that can adjust overfitting and underfitting through, "distance-based regression." Overfitting often results in finding false patterns causing inaccurate results, so by having a new approach that minimizes overfitting, more accurate predictions can be derived. Then I will proceed with a test of my regression form and show additional ways to optimize the regression. Finally, I will apply my new technique to a specific data set to demonstrate its practical value.