Naive Bayes and Text Classification I - Introduction and Theory
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Abstract (arXiv)
Naive Bayes classifiers, a family of classifiers that are based on the popular Bayes' probability theorem, are known for creating simple yet well performing models, especially in the fields of document classification and disease prediction. In this article, we will look at the main concepts of naive Bayes classification in the context of document categorization.
Key facts. Cited by 5 papers in the map (data through 7 Oct 2026). First posted on arXiv 16 Oct 2014.
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Citing papers per year: 2021: 2; 2022: 2; 2023: 1.
5 papers.
- 2022Immersive Text Game and Personality Classificationcited by 2
- 2021Identifying COVID-19 Fake News in Social Mediacited by 1
- 2021ARTH: Algorithm For Reading Text Handily -- An AI Aid for People having Word Processing Issuescited by 0
- 2022Semantic Code Classification for Automated Machine Learningcited by 0
- 2023Revisiting the Role of Label Smoothing in Enhanced Text Sentiment Classificationcited by 0
- 2023Revisiting the Role of Label Smoothing in Enhanced Text Sentiment Classification11 Dec 2023
- 2022Immersive Text Game and Personality Classification20 Mar 2022
- 2022Semantic Code Classification for Automated Machine Learning25 Jan 2022
- 2021Identifying COVID-19 Fake News in Social Media28 Jan 2021
- 2021ARTH: Algorithm For Reading Text Handily -- An AI Aid for People having Word Processing Issues23 Jan 2021