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locality-sensitive-hashing

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bensums
bensums commented Mar 21, 2020

Is there a default seed? I copied the Python code from seed_test.py and removed the set_seed calls. The test passed thousands of times despite no set_seed calls being made. Is this expected? If so, can we document this? Is there an explicit default seed?

Just as a sanity check, I modified the calls to set the seed to two distinct values and it failed every time, as expected.

The reason I'm a

duncster94
duncster94 commented Feb 27, 2020

Thanks for the library and excellent documentation.

I have ~30 million documents that I've computed LeanMinHashes for. I want to essentially create a graph of documents where each edge corresponds to two documents sharing a Jaccard similarity above the threshold specified in the MinHashLSH object. This means calling lsh.query(doc_i_minhash) for each document i.

The problem I'm having

ivanshilo
ivanshilo commented Apr 29, 2019

Hi,
I suggest you update Documentation page with a better explanation regarding windows.
I do not know how things are going with installation through Python environment, but direct compilation of library is not possible not because you do not provide Visual Studio project or something but because FHHT is mostly written in inline assembler code that is supported by GCC/Clang compilers only.

Dice.com repo to accompany the dice.com 'Vectors in Search' talk by Simon Hughes, from the Activate 2018 search conference, and the 'Searching with Vectors' talk from Haystack 2019 (US). Builds upon my conceptual search and semantic search work from 2015

  • Updated Feb 12, 2020
  • Python

Built text and image clustering models using unsupervised machine learning algorithms such as nearest neighbors, k means, LDA , and used techniques such as expectation maximization, locality sensitive hashing, and gibbs sampling in Python

  • Updated Jan 20, 2018
  • Jupyter Notebook

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