🏡 💰 📈 House Prices

https://www.kaggle.com/c/house-prices-advanced-regression-techniques

This Kaggle competition is aimed at predicting the final price of houses with 79 explanatory variables describing (almost) every aspect of residential homes in Ames, Iowa.

Dataset info

• train.csv - the training set
• test.csv - the test set
• data_description.txt - full description of each column, originally prepared by Dean De Cock but lightly edited to match the column names used here
• sample_submission.csv - a benchmark submission from a linear regression on year and month of sale, lot square footage, and number of bedrooms

Using:

• Data preprocessing
• Feature engineering
• Models training: RidgeCV, LassoCV, GradientBoostingRegressor

Result

I get best results (821 place out of 5172) from blending 2 models: RidgeCV and LassoCV in a ratio of 90/10.