This project is created for Kaggle competition - House Prices: Advanced Regression Techniques. It uses ensembling of XGboost and LightGBM models to make predictions.
- Competition data set in Kaggle.
- XGBoost
- LightGBM
- scikit-learn
These instructions will get you a brief idea on setting up the environment and running on your local machine for development and testing purposes.
Prerequisities
- python3.5 or newer
- XGBoost
- LightGBM
- scikit-learn
- numpy
- pandas
- seaborn
- matplotlib
- statsmodels
Setup and running tests
-
Run
python -V
to check the installation -
Install all the required libraries.
-
Execute the following commands from terminal to run the tests:
python main.py
Note: Submission score is 0.12544 LB. Further improvement is definitely possible.