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Locality-sensitive hashing to implement K nearesr neighbors fast.

Project description

HasedKNN

LSH based KNN inspired from LSH Attention (Reformer: The Efficient Transformer)

Last Stable Release

$ pip install hashedknn

Usage example

From a jupyter notebook run

import HashedKNN

# Fetch dataset
from sklearn.datasets import fetch_openml
X, y = fetch_openml('mnist_784', version=1, return_X_y=True)

# Run LSH based KNN
knn = HasedKNN(bucket_size=8, number_of_universes=20)

# Fit
knn.fit(X)

# Find ID's of 10 nearest neighbors
id = knn.find(vectorIdx=10, corpus=X, k=10)

Project details


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Files for HashedKNN, version 1.0.0
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