title	emoji	colorFrom	colorTo	sdk	sdk_version	app_file	pinned
Mockml - House Price Predictor	🏠	indigo	yellow	gradio	5.23.3	main.py	false

🏠 House Price Predictor

This is find the model which uses ML challenge!

1. A rule-based model that uses a logical formula to estimate house prices.
2. A machine learning model trained on synthetic housing data.

Both models predict house prices based on three input features:

• Square meters of the house.
• Number of bedrooms in the house.
• Distance from the city center (in kilometers).

Along with Price (in €), the app also provides a confidence score for each prediction, indicating how reliable the prediction is.

---

📊 Formula for Calculating Price

The rule-based model uses the following formula to calculate house prices:

price = 400 + 0.15 * sqmt + 200 * bedrooms - 5.5 * distance + bonuses - penalties

Where:

• sqmt: Square meters of the house (clipped between 15 and 200).
• bedrooms: Number of bedrooms (clipped between 1 and 6).
• distance: Distance from the city center in kilometers (clipped between 0.1 and 50).
• Bonuses:
  • +400 if sqmt > 140 and bedrooms > 3.
• Penalties:
  • -100 if sqmt < 30 and bedrooms < 2.

The final price is clipped between €400 and €3000.

---

🚀 How to Access the App Demo?

You can access the app demo on Hugging Face Spaces:

👉 Try the House Price Predictor

📚 Dependencies

This app uses the following Python libraries:

• gradio
• numpy
• pandas
• scikit-learn
• joblib

Make sure to install them before running the app locally.

---

🧑‍💻 Run Locally

To run the app locally:

1. Clone this repository.
2. Install dependencies using pip install -r requirements.txt.
3. Run the app with python main.py.
4. Open the app in your browser at http://127.0.0.1:7860.

Enjoy a tiny challenge!