NLP-based Reuters-21578 Automated News Classification with Naive Bayes
Read this in other languages: English, Turkish.
This code block executes an NLP project on the Reuters-21578 dataset. The project aims to classify news articles according to specific topics (e.g. grain money-fx earn etc.). The code uses various Python libraries such as pandas numpy re os and sklearn. The project uses different methods and functions for data loading preprocessing and classifier model training. The preprocessing steps include various methods to clean process and vectorize the text data. The classifier model is trained on the training data using the Naive Bayes algorithm. Then the trained model is used to make predictions on the test data and the results are evaluated using different performance metrics (confusion matrix accuracy_score etc.). This code block can be used for NLP projects and it may produce different results when applied to different datasets.
đź’» Built with
Technologies used in the project:
- Python
- BERT
- Jupyter Notebook
- Anaconda
- NLP