Kaggle: House Prices: Advanced Regression Techniques

This Repo contains the code and data I used in the Kaggle Competition House Prices - Advanced Regression Techniques.

Data

• train.csv - the training set, 1460 houses with 81 attributes, including the labels (sale prices)
• test.csv - the test set, 1459 houses with 80 attributes
  
• data_description.txt - full description of each column

Results

Explorotory Data Analysis, Feature Engineering and a solution based on different base models and ensemble models (stacking, blending) are shown in house-prices.ipynb.

Required libraries

• NumPy
• Pandas
• scipy
• scikit-learn
• matplotlib
• scikit-learn
• XGBoost
• LightGBM
• mlxtend