generall / sklearn-sknnsuite

Wrapper which provides scikit-learn-compatible implementation of SkNN sequence labeling algorithm

Hi, it's Andrey

I'm a Machine Learning Engineer. I prefer practical over theoretical, working demo over arXiv paper.

Currently working on a Vector Similarity Search Engine Qdrant, which can be used for semantic search, similarity matching of text, images or even videos, and also recommendations.

My CV is here. I also have a blog and a telegram channel

My interests and projects

• Self-supervised and transfer learning in NLP [ blog posts 🔗 ]
• Matching models [ blog posts 🔗 ]
• Knowledge extraction [ project 🔗 ]
• NN powered search engines [ blog posts 🔗, 🔗 ] & [ repo 🔗 ]
• Functional programming and Rust

📫 Feel free to reach me with email or telegram

sklearn-sknnsuite's Issues

CoNLL2000 example

Hello @generall ,

Thank you for this awesome project, paper and code base.

I´m always looking for algorithms that can surpass the CRFSuite for a sequential labeling problem that I have. And your paper shows some promising results, with a very novel idea. Congratulations!!
I would love to see if applies to my problem.

In the paper you use some specific "distance functions" ( such as MVDM) and uses as context "Two elements before and after current one."

Could you please show an example in sknnsuite similar to this scenario ? With the actual code I can´t see an straightforward way to do it.

Thank you again!