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@@ -42,11 +42,23 @@ size_categories:
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  - 10K<n<100K
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  ---
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- Examples of preprcoessing algorithms:
 
 
 
 
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  - [spam_assassin.js](./spam_assassin.js), followed by [spam_assassin.py](./spam_assassin.py)
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  - [enron_spam.py](./enron_spam.py)
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  <br>
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- Deduplicated dataset statistics:
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- ![](./spam_counts.png)
 
 
 
 
 
 
 
 
 
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  - 10K<n<100K
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  ---
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+ This is a large corpus of 41,574 preprocessed sms spam messages and emails sent by humans in 32 languages.
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+ <br>
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+ ### Some preprcoessing algorithms
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  - [spam_assassin.js](./spam_assassin.js), followed by [spam_assassin.py](./spam_assassin.py)
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  - [enron_spam.py](./enron_spam.py)
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  <br>
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+ ### Data composition
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+ ![](./spam_counts.png)
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+ <br>
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+
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+ ### Original source
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+ - https://huggingface.co/datasets/sms_spam
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+ - https://github.com/MWiechmann/enron_spam_data
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+ - https://www.kaggle.com/datasets/ganiyuolalekan/spam-assassin-email-classification-dataset