Ask HN: What’s the optimal approach for KNN (K- Nearest Neighbor)? 6 pointstrifit3 years ago2 commentsSaveHideCopy link On HNComments−PaulHoule3yDepends on what you want to optimize for. See this paperhttps://arxiv.org/abs/1702.08734And this library that it describeshttps://github.com/facebookresearch/faissWhich is an optimal use of your time as you can install it in a minute with anaconda if you use Python.−eesmith3yIn 2D? 3D? <10D? In high-dimensional space?Binary, continuous, or count vectors, or a mix? Or something more novel?What's your distance or similarity method?Is there a bound to your search?Exact or approximate? If approximate, what counts as good enough?All of these affect "optimal".
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Depends on what you want to optimize for. See this paper
https://arxiv.org/abs/1702.08734
And this library that it describes
https://github.com/facebookresearch/faiss
Which is an optimal use of your time as you can install it in a minute with anaconda if you use Python.
In 2D? 3D? <10D? In high-dimensional space?
Binary, continuous, or count vectors, or a mix? Or something more novel?
What's your distance or similarity method?
Is there a bound to your search?
Exact or approximate? If approximate, what counts as good enough?
All of these affect "optimal".