Code for "Performance shootout between nearest-neighbour libraries": http://radimrehurek.com/2013/11/performance-shootout-of-nearest-neighbours-intro
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wikisim_server
.gitignore
LICENSE
README.md
plots.py
prepare_shootout.py
requirements.txt
run_all.sh
shootout.py
shootout_annoy.py
shootout_flann.py
shootout_gensim.py
shootout_kgraph.py
shootout_lsh.py
shootout_sklearn.py

README.md

sim-shootout

Code for the blog series on benchmarking nearest-neighbour libraries:

Part I: Intro

Part II: Contestants

Part III: Querying

The target are libraries that expose a Python interface and allow (exact or approximate) k-NN search in high dimensional vector spaces.

Run run_all.sh to download Wikipedia, index it and run all experiments.