Comments (2)
Interesting, Are you referring to replace the library import to indigenous function? If that so, I have few questions:
- Why it is required to have our own function like as a broader picture Can you explain?
- How fast are we making the DameruLevenDist? Do you have any benchmark as of now?
- Are we also focusing on increasing the accuracy of the agent ?
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@Kaushl2208
Currently Atarashi depends upon pyxDamerauLevenshtein library which has no further development and lacks proper maintenance of the codebase. Implementing the same edit distance natively will give us more flexibility in terms of customisation and maintenance and will make Atarashi less dependent.
Also, I'll be applying the method similar to the currently implemented one so the accuracy should remain more or the same but we can surely look for the ways to improve it.
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Related Issues (20)
- build dependencies are not getting install properly
- Build fails HOT 14
- Make the code PEP8 compliant HOT 2
- Run the evaluator command without any 'similarity' parameter HOT 2
- Shift from argparse module to plac command line parser. HOT 3
- Parallelize the evaluator algorithm HOT 5
- [Proposal] Improve the speed of matching HOT 1
- Pipfile: the replacement for requirements.txt HOT 9
- Pandas error at run: pandas.errors.ParserError HOT 1
- ModuleNotFoundError occurs when running after installing with pip. HOT 3
- Broken Link in README.md
- Ability to scan directories HOT 22
- Invalid File Path in Atarashi HOT 4
- List Index Out of Range HOT 3
- FEAT: Increasing the overall performance of Atarashi HOT 1
- Build fails due to import error from nirjas HOT 1
- Error in CommentPreprocessor
- Improve TF-IDF agent by tuning matches threshold HOT 1
- Make evaluation.py more informative
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