Polish House Price Prediction Dataset Overview

Dataset Structure

• data/: Contains the raw dataset Houses.csv and preprocessed data files X_train.csv, X_test.csv, y_train.csv, y_test.csv.
• models/: Stores trained models, including linear_regression_model.pkl and knn_model.pkl.
• src/: Contains source code for data preprocessing, model training, and evaluation, such as preprocessing.py, linear_regression.py, knn.py, main.py.
• notebooks/: Contains Jupyter notebooks for exploratory data analysis and model building, EDA.ipynb and Modeling.ipynb.

Model Information

1. Linear Regression Model:

   • Trained using scikit‑learn's LinearRegression.
   • Model saved as models/linear_regression_model.pkl.
   • Evaluation metrics include mean squared error, R² score, and cross‑validation score.

2. K‑Nearest Neighbors (KNN) Model:

   • Trained using scikit‑learn's KNeighborsRegressor.
   • Model saved as models/knn_model.pkl.
   • Evaluation metrics include mean squared error, R² score, and cross‑validation score.

Future Improvement Directions

• Hyperparameter tuning: Try different configurations to improve model performance.