This repository contains the results of experiments I conducted on a dataset of recipes by region. For more information, check out the IPython Notebook (ipynb) file.
Dataset comes from: http://www.nature.com/articles/srep00196, a research paper on food pairings.
Direct download link: http://www.nature.com/article-assets/npg/srep/2011/111215/srep00196/extref/srep00196-s3.zip
This repository makes heavy use of the Scikit-Learn library for its classifiers, along with the Numpy and Pandas libraries for working with arrays and dataframes. All of these libraries come with Anaconda ( https://store.continuum.io/cshop/anaconda/ ) or can easily be installed through pip.
The Ipython Notebook has its own dependencies to run, which can be read about more here: https://jupyter.readthedocs.org/en/latest/install.html . My notebook also includes its own additional dependencies for creating graphs. These include Matplotlib and Seaborn. Again, each of these libraries are available through either pip or conda.