# Backronym

## TL;DR

This paper introduces the concept of inheritance among machine learning models to streamline research, reduce information overload, and uncover previously unnoticed models, fostering innovation and easier dissemination of methods.

## Contribution

It proposes a novel inheritance framework for ML models that simplifies research and enhances discovery of overlooked methods.

## Key findings

- Model inheritance reduces research complexity.
- Uncovers previously unnoticed models.
- Facilitates easier publication of methods.

## Abstract

The field of Machine Learning research is divided into subject areas, where each area tries to solve a specific problem, using specific methods. In recent years, borders have almost been erased, and many areas inherit methods from other areas. This trend leads to better results and the number of papers in the field is growing every year. The problem is that the amount of information is also growing, and many methods remain unknown in a large number of papers. In this work, we propose the concept of inheritance between machine learning models, which allows conducting research, processing much less information, and pay attention to previously unnoticed models. We hope that this project will allow researchers to find ways to improve their ideas. In addition, it can be used by researchers to publish their methods too. Project is available by link: https://www.infornopolitan.xyz/backronym