https://github.com/offchan42/thai-thesis-classification

Classify each document inside the corpus using Python machine learning module: scikit-learn
https://github.com/offchan42/thai-thesis-classification

nlp python python2 scikit-learn segment thai thai-language thai-thesis-classification

Last synced: 7 days ago
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Classify each document inside the corpus using Python machine learning module: scikit-learn

• Host: GitHub
• URL: https://github.com/offchan42/thai-thesis-classification
• Owner: offchan42
• License: apache-2.0
• Created: 2016-06-08T13:07:50.000Z (over 8 years ago)
• Default Branch: master
• Last Pushed: 2018-08-02T18:57:10.000Z (over 6 years ago)
• Last Synced: 2024-03-02T00:39:03.771Z (8 months ago)
• Topics: nlp, python, python2, scikit-learn, segment, thai, thai-language, thai-thesis-classification
• Language: Jupyter Notebook
• Homepage: https://docs.google.com/presentation/d/1_58l-VVzTJN0Wr7IIu11eNf-ulLGPdsMG3MKg8DWgGU/edit?usp=sharing
• Size: 11.9 MB
• Stars: 1
• Watchers: 4
• Forks: 4
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • Changelog: change-file-encoding.ipynb
  • License: LICENSE

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README

        
# Thai-thesis-classification

Classify each document based on its actual class. _Supervised Learning_ :sparkles: 

All .ipynb files can be opened using IPython notebook (currently known as Jupyter notebook)

## Follow files in this order:

 1. change-file-encoding

 2. segment-words

 3. classify-docs

 4. segment-words-unlabeled

 5. predict-new-docs

 6. predict-plagiarism-docs