Regression Analysis Suite

This repository contains Python implementations of regression models used for predictive modelling and statistical analysis. The scripts demonstrate the end-to-end pipeline of data preprocessing, model training, and performance evaluation.

                                           Scripts Overview

1. Test_Regression_Ver1.py

Purpose: Initial implementation of regression logic.

Focus: Basic model fitting and baseline metrics.

Key Features: Data loading, feature scaling, and standard error calculations.

2. Test_Regression_Ver2.py

Purpose: Iterative improvement or alternative model testing.

Focus: Comparative analysis or hyperparameter adjustments.

Key Features: Refined data handling and potentially different regression algorithms (e.g., Multiple Linear Regression vs Polynomial).

3. Requirements:

To run these scripts, ensure you have the following dependencies installed:

Python 3.x

NumPy

Pandas

Scikit-Learn

Matplotlib / Seaborn (for visualisation)

Bash: pip install numpy pandas scikit-learn matplotlib

5. Usage: Run the scripts via the terminal:

Bash: python "Test_Regression_ver1.py" python "Test_Regression_ver2.py"