This repository provides a comprehensive implementation of non-linear regression using machine learning algorithms. Non-linear regression is a powerful technique used to model complex relationships between variables when the relationship cannot be accurately represented by a linear model.
In this project, we explore various machine learning algorithms and techniques to perform non-linear regression. These algorithms can be used to estimate the parameters of a non-linear model based on a given dataset, enabling us to make predictions and gain insights into the underlying relationships between the variables.
To use the code in this repository, follow these steps:
Clone this repository
Install python and its libraries
I am using Linear, Quadratic Exponential and Power function model in it.
I am using boston data set for housing in this project.
At the end quadratic gave the best result for us.
Contributions to this repository are always welcome. If you find any issues, have suggestions for improvements, or would like to add new features or algorithms, please feel free to submit a pull request.