CSE4212: Machine Learning Lab

This repository contains my lab works for CSE4212 – Machine Learning Lab, focused on implementing and comparing machine learning algorithms using the Iris dataset.

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Experiments Overview

1️⃣ Logistic Regression vs Multinomial Naive Bayes

• Compared two classification algorithms on the same dataset.
• Evaluated model performance using accuracy, precision, recall, F1-score, and confusion matrices.
• Visualized feature importance and correlation heatmaps.

2️⃣ SVM vs Random Forest

• Trained and tested SVM (with linear kernel) and Random Forest models.
• Compared based on accuracy, precision, recall, and F1-score.
• Showed data distribution and feature importance for both models.

3️⃣ K-Means vs Gaussian Mixture Model (GMM)

• Performed unsupervised clustering on the dataset.
• Evaluated performance using Adjusted Rand Index (ARI).
• Visualized clusters using PCA for dimensionality reduction.

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