esmat12/egyptian-real-estate-price-predictor

Egyptian Real Estate Price Predictor

This is a RandomForestRegressor model trained to predict real estate prices in Egypt.

Model Details

• Algorithm: RandomForestRegressor
• Target: Property Price (EGP)
• Features: Includes cleaned and engineered features like size_sqm, bedrooms, bathrooms, down_payment, location, property type, payment method, and date-based features.

Performance Metrics (from evaluation on test set):

• MAE: 327,235.08
• MSE: 9,414,061,483,051.53
• RMSE: 3,068,234.26
• R2 Score: 0.9776

How to Use

from huggingface_hub import hf_hub_download
import joblib
import pandas as pd

# Download the model file
model_path = hf_hub_download(repo_id="esmat12/egyptian-real-estate-price-predictor", filename="random_forest_regressor_model.joblib")

# Load the model
loaded_model = joblib.load(model_path)

# Example prediction (make sure your input features match the training data format)
# X_test and X_train are available from your Colab session if you run this code in the same session
# For new data, you'd need to preprocess it exactly like your training data.

# For demonstration, let's use a sample from X_test
sample_input = pd.DataFrame(X_test.iloc[0:1]) # Ensure it's a DataFrame with correct columns

prediction = loaded_model.predict(sample_input)
print(f"Predicted price for sample: {prediction[0]:,.2f} EGP")