Summary of results may be found here: https://docs.google.com/document/d/17UUAweMWBC5K7yGNm9FLFASn2LdhuHec4Ew-loJSExs/edit?usp=sharing
To install this package you will need the 'conda', or another virtual environment.
Conda is the one that I used which now has the name miniconda
and is downloadable here
https://conda.io/miniconda.html
conda create --name=hprice python=2.7.13
conda activate hprice
- From this directory install all relevant packages:
pip install -r requirements.txt
conda instal jupyter
- Complile code:
python setup.py develop
Non-standard packages installed are: https://github.com/scikit-learn-contrib/sklearn-pandas
Given a csv file, with housing prices that we wish to predict, we use the full command:
predict_pricesi -i data/single_family_home_prices_to_predict.csv
or -i < your file>
that is in the same format as the
Please feel free to look at the improved_pipeline.ipynb
, though realize that it is an exploration-style notebook and not intended for presentation purposes.