Particle Swarm Optimization (PSO) Hyperparameter Optimization

This project demonstrates the use of Particle Swarm Optimization (PSO) for hyperparameter optimization of machine learning models in classification task.

Introduction

In this project, we use PSO to optimize the hyperparameters of various machine learning models, including K-Nearest Neighbors (KNN), Random Forest (RF), Decision Tree (DT), and Support Vector Classifier (SVC).

Requirements

• Python 3.x
• Required Python packages: numpy, joblib, scikit-learn, tqdm

Usage

1. Install the pso-optimizer library:

pip install pso-optimizer

2. Example usage is in main.py file.

Files

• main.py: The main script to run PSO hyperparameter optimization.
• pso_optimizer.py: Contains the PSOOptimizer class for PSO optimization.
• hyperparameter_mappings.py: Contains mappings for hyperparameters used in different machine learning models.
• README.md: This file.