https://github.com/injamul3798/bangla-newspaper-categorization-using-ml-models
In my Bangla news categorization project, I utilized XGBoost for efficient pattern recognition, SVM for handling non-linear relationships, and an ensemble of Random Forest, AdaBoost, and Logistic Regression to collectively enhance precision. This diverse approach ensures robust and accurate classification of Bangla news articles.
https://github.com/injamul3798/bangla-newspaper-categorization-using-ml-models
adaboostclassifier logistic-regression ml nlp sentiment-analysis svm text-classification xgboost-classifier
Last synced: 3 months ago
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In my Bangla news categorization project, I utilized XGBoost for efficient pattern recognition, SVM for handling non-linear relationships, and an ensemble of Random Forest, AdaBoost, and Logistic Regression to collectively enhance precision. This diverse approach ensures robust and accurate classification of Bangla news articles.
- Host: GitHub
- URL: https://github.com/injamul3798/bangla-newspaper-categorization-using-ml-models
- Owner: injamul3798
- Created: 2023-12-25T13:16:46.000Z (almost 2 years ago)
- Default Branch: master
- Last Pushed: 2023-12-25T13:24:18.000Z (almost 2 years ago)
- Last Synced: 2025-04-02T00:27:17.494Z (6 months ago)
- Topics: adaboostclassifier, logistic-regression, ml, nlp, sentiment-analysis, svm, text-classification, xgboost-classifier
- Language: Jupyter Notebook
- Homepage:
- Size: 654 KB
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
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README
Utilizing XGBoost for pattern recognition, SVM for non-linear relationships, and an ensemble of Random Forest, AdaBoost, and Logistic Regression, my Bangla news categorization achieves precision through diverse modeling. This comprehensive approach ensures accurate classification, capturing linguistic nuances and cultural references in Bangla news articles.
Dataset Link: https://www.kaggle.com/datasets/furcifer/bangla-newspaper-dataset/data
Project done by:
Md. Injamul Haque &&
Shakil Rana