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update compare benchmarks
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guoyongzhi committed Sep 10, 2023
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Expand Up @@ -63,21 +63,21 @@ We tested four language identification packages: `LanguageIdentification.jl` (th
We calculated the average accuracy for the languages supported by multiple packages, and the results are as follows:
- tatoeba

| | 50 languages | 39 languages | 35 languages | 24 languages |
|-------------------------------|--------------|--------------|--------------|--------------|
| **LanguageIdentification.jl** | **94.58%** | **94.24%** | **93.77%** | **95.87%** |
| Languages.jl | - | 74.72% | 73.65% | 74.14% |
| LanguageDetect.jl | - | - | 80.81% | 80.61% |
| LanguageFinder.jl | - | - | - | 79.70% |
| | 50 languages | 39 languages | 38 languages | 35 languages | 24 languages |
|-------------------------------|--------------|--------------|--------------|--------------|--------------|
| LanguageIdentification.jl | **94.58%** | **94.24%** | **93.89%** | **93.77%** | **95.87%** |
| Languages.jl | - | 74.72% | - | 73.65% | 74.14% |
| LanguageDetect.jl | - | - | 79.72% | 80.81% | 80.61% |
| LanguageFinder.jl | - | - | - | - | 79.70% |

- wikipedia

| | 50 languages | 39 languages | 35 languages | 24 languages |
|-------------------------------|--------------|--------------|--------------|--------------|
| **LanguageIdentification.jl** | **98.20%** | **98.22%** | **98.09%** | **98.79%** |
| Languages.jl | - | 95.12% | 94.80% | 95.02% |
| LanguageDetect.jl | - | - | 85.49% | 86.23% |
| LanguageFinder.jl | - | - | - | 94.75% |
| | 50 languages | 39 languages | 38 languages | 35 languages | 24 languages |
|-------------------------------|--------------|--------------|--------------|--------------|--------------|
| LanguageIdentification.jl | **98.20%** | **98.22%** | **98.14%** | **98.09%** | **98.79%** |
| Languages.jl | - | 95.12% | - | 94.80% | 95.02% |
| LanguageDetect.jl | - | - | 85.36% | 85.49% | 86.23% |
| LanguageFinder.jl | - | - | - | - | 94.75% |

# Parameter Tuning
You can manually initialize the package using the `LanguageIdentification.initialize` function. By adjusting the parameters, you can achieve different balances between accuracy, speed, and memory usage. The default setting is `ngram=1:4`, `cutoff=0.85`, and `vocabulary=1000:5000`. However, this setting may not be optimal for your specific use case.
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Registration pull request created: JuliaRegistries/General/91147

After the above pull request is merged, it is recommended that a tag is created on this repository for the registered package version.

This will be done automatically if the Julia TagBot GitHub Action is installed, or can be done manually through the github interface, or via:

git tag -a v1.0.0 -m "<description of version>" e4914167196a7bb9b6c92d57b8eacdccf97c28b0
git push origin v1.0.0

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