PhDP / EcoInter

Manuscript, code and data for the paper "Ecological Interactions and the Netflix Problem"

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Ecological Interactions and the Netflix Problem

This repository contains:

  • KNN: C++ code for the K nearest neighbor recommender and imputer.
  • Supervised Learning contains the Python script for random forests.
  • Figures contain figures (yeah, really) and Python/R scripts to generate them.

THe KNN and Supervised Learning folders contains the formatted data used for the article.

Data

The data used for this research was taken from:

C Digel, A Curtsdotter, J Riede, B Klarner, and U Brose. Unravelling the complex structure of forest soil food webs: higher omnivory and more trophic levels. In Oikos, volume 123, pages 1157–1172, 2014.

The authors licensed the data under the Creative Commons CC BY-NC-SA.

Code

The C++ and Python code are license under the liberal MIT license.

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Manuscript, code and data for the paper "Ecological Interactions and the Netflix Problem"


Languages

Language:C++ 89.0%Language:TeX 8.0%Language:Python 1.9%Language:CMake 0.7%Language:R 0.2%Language:Shell 0.1%Language:Makefile 0.1%