Machine Learning Assignment

This project implements demo programs for the algorithms listed in your assignment:

• Clustering: K-means, Modified K-means, Hierarchical, Fuzzy C-means
• Density-based learning: DBSCAN, HDBSCAN
• Semi-supervised learning: self-training
• Ensemble learning: Random Forest Regressor, Random Forest Classifier, XGBoost, AdaBoost, CatBoost
• Multilayer Perceptron (MLP)
• Recurrent Neural Network (RNN)
• Self-Organizing Map (SOM)
• Hidden Markov Model (HMM)
• Support Vector Machine (SVM)
• Large Language Model (LLM)
• Generalized Regression Neural Network (GRNN)

Setup

cd c:\Users\misba\OneDrive\Desktop\ML_Assignment
python -m venv .venv
.\.venv\Scripts\Activate.ps1
pip install -r requirements.txt

Run

Show all options:

python ml_assignment.py --help

Run one demo:

python ml_assignment.py --algo kmeans
python ml_assignment.py --algo fuzzy_cmeans
python ml_assignment.py --algo rnn
python ml_assignment.py --algo llm

Run everything:

python ml_assignment.py --algo all

Notes

• hdbscan, xgboost, catboost, torch, and transformers can be heavy installs.
• LLM demo downloads a small model (distilgpt2) the first time.
• GRNN is implemented from first principles using Gaussian kernel regression.