# 🏌️ Golf Decision using Naive Bayes Classifier (BNB)

This repository presents a simple implementation of the **Naive Bayes Classifier** in Java for the classic **golf decision dataset**, where the model predicts whether to play golf based on weather conditions such as outlook, temperature, humidity, and wind.

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## 🧠 Algorithm

- **Naive Bayes** (Bernoulli variant)
- Probabilistic classifier based on Bayes' Theorem with independence assumptions
- Handles categorical input features efficiently

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## 🗃️ Dataset Structure

| Outlook  | Temperature | Humidity | Wind   | PlayGolf |
|----------|-------------|----------|--------|----------|
| Sunny    | Hot         | High     | Weak   | No       |
| Overcast | Mild        | Normal   | Strong | Yes      |
| Rainy    | Cool        | High     | Weak   | No       |
| ...      | ...         | ...      | ...    | ...      |

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## 📂 Project Structure

GolfDecision-BNB/ ├── src/ │ └── Main.java │ └── NaiveBayesClassifier.java │ └── Dataset.java ├── dataset.csv └── README.md

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## 🚀 How to Run

1. Compile the program:
```bash
javac -d bin src/*.java

2. Run the classifier:

java -cp bin Main

The classifier will train on the dataset and output prediction results for new examples.

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📈 Sample Output

Training accuracy: 92.3%
Predicting new sample: {Sunny, Cool, High, Strong}
→ Result: No

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📚 Learning Outcomes

• Understand how Naive Bayes works on categorical datasets
• Gain experience in implementing probabilistic models in Java
• See real application on decision-based problems

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👨‍💻 Author

Do Nguyen Anh Tuan 🎓 MSc Student in IT @ Lac Hong University 🏢 FabLab @ EIU 🔗 Portfolio Website