🔍 Find-S Algorithm

This project implements the Find-S Algorithm, a concept learning algorithm used in Machine Learning to determine the most specific hypothesis that is consistent with all positive training examples.

✨ Features

• 📂 Load training data from a CSV file
• 🤖 Implement the Find-S Algorithm from scratch
• 🎯 Find the most specific hypothesis
• 📊 Display the final hypothesis based on positive examples

🛠️ Technologies Used

• 🐍 Python
• 🐼 Pandas

📁 Dataset

• Training_examples.csv containing training examples with attributes and a target class (Yes/No).

🚀 How It Works

1. 📥 Read the training dataset.
2. ✅ Select the first positive example as the initial hypothesis.
3. 🔄 Compare it with other positive examples and generalize mismatched attributes using ?.
4. 📈 Output the final most specific hypothesis.

📌 Output

• 📝 Most specific hypothesis that correctly classifies all positive training examples.