Iris Flower Classification Optimization using PSO & GWO

Overview

This project applies two meta-heuristic optimization algorithms:

Particle Swarm Optimization (PSO)

Grey Wolf Optimizer (GWO)

to optimize the hyperparameters of a Random Forest classifier for Iris flower classification.

The project was developed as part of the Optimization Techniques course.

Objective

The main goal was to improve classification accuracy by automatically tuning Random Forest hyperparameters instead of using manual parameter selection.