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User Guide / Tutorial:

  • How to use PyNNDescent
  • PyNNDescent with different metrics
  • Working with sparse data
  • Working with Scikit-learn pipelines

Background

  • How PyNNDescent works
  • PyNNDescent Performance

API Reference:

  • PyNNDescent API Guide
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  • Docs »
  • Index
  • Edit on GitHub

Index

C | E | F | M | N | P | Q | S | T | U | W

C

  • chebyshev (in module pynndescent.distances)

E

  • euclidean (in module pynndescent.distances)

F

  • fit() (pynndescent.pynndescent_.PyNNDescentTransformer method)
  • fit_transform() (pynndescent.pynndescent_.PyNNDescentTransformer method)

M

  • manhattan (in module pynndescent.distances)
  • minkowski (in module pynndescent.distances)

N

  • NNDescent (class in pynndescent.pynndescent_)

P

  • pynndescent.distances (module)
  • PyNNDescentTransformer (class in pynndescent.pynndescent_)

Q

  • query() (pynndescent.pynndescent_.NNDescent method)

S

  • squared_euclidean (in module pynndescent.distances)
  • standardised_euclidean (in module pynndescent.distances)

T

  • transform() (pynndescent.pynndescent_.PyNNDescentTransformer method)

U

  • update() (pynndescent.pynndescent_.NNDescent method)

W

  • weighted_minkowski (in module pynndescent.distances)

© Copyright 2020, Leland McInnes Revision cb5fa2e0.

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