k nearest neighbor (KNN) graphs via Pearson correlation distance and local sensitive hashing (LSH).
Development: https://github.com/iosonofabio/lshknn
Authors: Fabio Zanini and Paolo Carnevali
License: MIT
Copyright: Fabio Zanini and Chan Zuckerberg Initiative
import numpy as np
import lshknn
# Make mock data
# 2 features (rows), 4 samples (columns)
data = np.array(
[[1, 0, 1, 0],
[0, 1, 0, 1]],
dtype=np.float64)
# Instantiate class
c = lshknn.Lshknn(
data=data,
k=1,
threshold=0.2,
m=10,
slice_length=4)
# Call subroutine
knn, similarity, n_neighbors = c()
# Check result
assert (knn == [[2], [3], [0], [1]]).all()1 maintainer
Metadata
1 maintainer
Release files for lshknn 0.1.2
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